The role of liver cancer stem cells in hepatocellular carcinoma metastasis

Metastasis accounts for the vast majority of cancer deaths; however, this complex process has yet to be fully explained. To form metastases, cancer cells must undergo a series of steps, known as the "Metastatic cascade", each of which requires a specific functional transformation. Cancer stem cells (CSCs) play a vital role in tumor metastasis, but their dynamic behavior and regulatory mechanisms have not been fully elucidated. Based on the "Metastatic cascade" theory, this review summarizes the effect of liver CSCs on the metastatic biological programs that underlie the dissemination and metastatic growth of cancer cells. Liver CSCs have the capacity to initiate distant organ metastasis via EMT, and the microenvironment transformation that supports the ability of these cells to disseminate, evade immune surveillance, dormancy, and regenerate metastasis. Understanding the heterogeneity and traits of liver CSCs in these processes is critical for developing strategies to prevent and treat metastasis of advanced hepatocellular carcinoma (HCC).

Alterations in serum metabolic profiles of early-stage hepatocellular carcinoma patients after radiofrequency ablation therapy

OBJECTIVE

To investigate the alterations in serum metabolic profiles and early-stage hepatocellular carcinoma (HCC) patient characteristics after radiofrequency ablation (RFA) therapy. This evaluation aimed to assess treatment effectiveness and identify potential novel approaches and targets for HCC treatment and prognosis monitoring.

METHODS

Untargeted metabolomics technology was employed to analyze serum metabolic profiles in healthy volunteer controls (NCs) and early stage HCC patients before and after RFA therapy. Additionally, Human Metabolome Database and Kyoto Encyclopedia of Genes and Genomes database were used to identify the differential metabolites (DMs) and metabolic pathways. Cystoscape was utilized to construct DM gene networks. Amino acid analyses were performed to validate our findings.

RESULTS

We identified 11, 14, and six DMs between the NC and HCC groups, HCC patients before and after RFA therapy, and post-RFA HCC and NC groups, respectively. The expression levels of these DMs, particularly those of amino acids and lipids, significantly changed. Compared with the NC group, higher levels of L-tyrosine, aspartate, and 18-oxo-oleate were observed in HCC patients, which were significantly reduced in patients after RFA therapy. Meanwhile, HCC patients after RFA therapy had increased levels of L-arginine, phosphatidic acid (20:3), and lysophosphatidyl choline (LPC) (20:4) compared to those before therapy, while their levels before therapy were lower than those of NC. Moreover, most metabolites in the post-RFA and NC groups showed no significant changes in expression, except for L-tyrosine and LPC (16:0). These metabolites could potentially serve as characteristic factors of early-stage HCC patients after RFA therapy. Joint pathway analysis revealed striking changes, mainly in phenylalanine, tyrosine, and tryptophan biosynthesis; alanine, aspartate, and glutamate metabolism; and arginine and aminoacyl-tRNA biosynthesis. Bioinformatics analysis of publicly available data preliminarily identified 187 DM-related metabolic enzymes.

CONCLUSION

Our study proposed novel targets for early-stage HCC treatment, laying the groundwork for improving treatment efficacy and prognosis of early-stage HCC patients.

Comprehensive analysis and experimental verification of the mechanism of action of T cell-mediated tumor-killing related genes in Colon adenocarcinoma

BACKGROUND

Colorectal cancer (CRC) is a prevalent malignancy of the digestive tract. A new prognostic scoring model for colon adenocarcinoma (COAD) is developed in this study based on the genes involved in tumor cell-mediated killing of T cells (GSTTKs), accurately stratifying COAD patients, thus improving the current status of personalized treatment.

METHOD

The GEO and TCGA databases served as the sources of the data for the COAD cohort. This study identified GSTTKs-related genes in COAD through single-factor Cox analysis. These genes were used to categorize COAD patients into several subtypes via unsupervised clustering analysis. The biological pathways and tumor microenvironments of different subgroups were compared. We performed intersection analysis between different subtypes to obtain intersection genes. Single-factor Cox regression analysis and Lasso-Cox analysis were conducted to establish clinical prognostic models. Two methods are used to assess the accuracy of model predictions: ROC and Kaplan-Meier analysis. Next, the prediction model was further validated in the validation cohort. Differential immune cell infiltration between various risk categories was identified via single sample gene set enrichment analysis (ssGSEA). The COAD model's gene expression was validated via single-cell data analysis and experiments.

RESULT

We established two distinct GSTTKs-related subtypes. Biological processes and immune cell tumor invasion differed significantly between various subtypes. Clinical prognostic models were created using five GSTTKs-related genes. The model's risk score independently served as a prognostic factor. COAD patients were classified as low- or high-risk depending on their risk scores. Patients in the low-risk category recorded a greater chance of surviving. The outcomes from the validation cohort match those from the training set. Risk scores and several tumor-infiltrating immune cells were strongly correlated, according to ssGSEA. Single-cell data illustrated that the model's genes were linked to several immune cells. The experimental results demonstrated a significant increase in the expression of HOXC6 in colon cancer tissue.

CONCLUSION

Our research findings established a new gene signature for COAD. This gene signature helps to accurately stratify the risk of COAD patients and improve the current status of individualized care.

Prognostic biomarkers associated with immune checkpoint inhibitors in hepatocellular carcinoma

The treatment of hepatocellular carcinoma (HCC), particularly advanced HCC, has been a serious challenge. Immune checkpoint inhibitors (ICIs) are landmark drugs in the field of cancer therapy in recent years, which have changed the landscape of cancer treatment. In the field of HCC treatment, this class of drugs has shown good therapeutic prospects. For example, atezolizumab in combination with bevacizumab has been approved as first-line treatment for advanced HCC due to significant efficacy. However, sensitivity to ICI therapy varies widely among HCC patients. Therefore, there is an urgent need to search for determinants of resistance/sensitivity to ICIs and to screen biomarkers that can predict the efficacy of ICIs. This manuscript reviews the research progress of prognostic biomarkers associated with ICIs in HCC in order to provide a scientific basis for the development of clinically individualised precision medication regimens.

Application of artificial intelligence in the prediction of immunotherapy efficacy in hepatocellular carcinoma: Current status and prospects

Artificial Intelligence (AI) has increased as a potent tool in medicine, with promising oncology applications. The emergence of immunotherapy has transformed the treatment terrain for hepatocellular carcinoma (HCC), offering new hope to patients with this challenging malignancy. This article examines the role and future of AI in forecasting the effectiveness of immunotherapy in HCC. We highlight the potential of AI to revolutionize the prediction of therapy response, thus improving patient selection and clinical outcomes. The article further outlines the challenges and future research directions in this emerging field.

New advances in the study of PD-1/PD-L1 inhibitors-induced liver injury

The application of immune checkpoint inhibitors (ICIs) has made extraordinary achievements in tumor treatment. Among them, programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors can improve the prognosis of advanced tumors, and have been widely used in clinical practice to treat many types of cancers. However, excessive immune response can also induce immune-related adverse events (irAEs) involving many organs. Of these, immune-related liver injury is the relatively common and carries the highest morbidity, which has attracted the attention of hepatologists all over the world. The incidence of this type of liver injury depends specifically on factors such as the type of drug being combined, viral infection, type of cancer and liver transplantation. Although there is no unanimity on the mechanism of PD-1/PD-L1 inhibitor-induced liver injury, in this review, we also summarize the current evidence that provides insights into the pathogenesis of PD-1/PD-L1 inhibitor-induced liver injury, including the fact that PD-1/PD-L1 inhibitors cause reactivation of CTLs, aberrant presentation of autoantigens, hepatic immune tolerance environment is disrupted, and cytokine secretion, among other effects. Patients usually develop liver injury after the use of PD-1/PD-L1 inhibitors, and clinical symptoms mainly include weakness, muscle pain, nausea and vomiting, and jaundice. Histologically, the main manifestation is lobular hepatitis with lobular inflammatory infiltration. Since the specific biomarkers for PD-1/PD-L1 inhibitor-associated liver injury have not been identified yet, alpha-fetoprotein, IL-6, and IL-33 have the potential to be biomarkers for predicting this type of liver injury in the future, but this requires further research. We also describe the examination and treatment of this type of liver injury, which usually includes eliminating related influencing factors, regularly monitoring liver function, temporarily retaining or permanently stopping ICIs treatment according to the severity of toxicity, and using corticosteroids. This review may provide useful information for the future clinical practice of PD-1/PD-L1 inhibitors.

The Role of Extracellular Vesicles in the Treatment of Prostate Cancer

Prostate cancer (PCa) has become a public health concern in elderly men due to an ever-increasing number of estimated cases. Unfortunately, the available treatments are unsatisfactory because of a lack of a durable response, especially in advanced disease states. Extracellular vesicles (EVs) are lipid-bilayer encircled nanoscale vesicles that carry numerous biomolecules (e.g., nucleic acids, proteins, and lipids), mediating the transfer of information. The past decade has witnessed a wide range of EV applications in both diagnostics and therapeutics. First, EV-based non-invasive liquid biopsies provide biomarkers in various clinical scenarios to guide treatment; EVs can facilitate the grading and staging of patients for appropriate treatment selection. Second, EVs play a pivotal role in pathophysiological processes via intercellular communication. Targeting key molecules involved in EV-mediated tumor progression (e.g., proliferation, angiogenesis, metastasis, immune escape, and drug resistance) is a potential approach for curbing PCa. Third, EVs are promising drug carriers. Naïve EVs from various sources and engineered EV-based drug delivery systems have paved the way for the development of new treatment modalities. This review discusses the recent advancements in the application of EV therapies and highlights EV-based functional materials as novel interventions for PCa.

Gut Bacteria Provide Genetic and Molecular Reporter Systems to Identify Specific Diseases

With genetic information gained from next-generation sequencing (NGS) and genome-wide association studies (GWAS), it is now possible to select for genes that encode reporter molecules that may be used to detect abnormalities such as alcohol-related liver disease (ARLD), cancer, cognitive impairment, multiple sclerosis (MS), diabesity, and ischemic stroke (IS). This, however, requires a thorough understanding of the gut-brain axis (GBA), the effect diets have on the selection of gut microbiota, conditions that influence the expression of microbial genes, and human physiology. Bacterial metabolites such as short-chain fatty acids (SCFAs) play a major role in gut homeostasis, maintain intestinal epithelial cells (IECs), and regulate the immune system, neurological, and endocrine functions. Changes in butyrate levels may serve as an early warning of colon cancer. Other cancer-reporting molecules are colibactin, a genotoxin produced by polyketide synthetase-positive Escherichia coli strains, and spermine oxidase (SMO). Increased butyrate levels are also associated with inflammation and impaired cognition. Dysbiosis may lead to increased production of oxidized low-density lipoproteins (OX-LDLs), known to restrict blood vessels and cause hypertension. Sudden changes in SCFA levels may also serve as a warning of IS. Early signs of ARLD may be detected by an increase in regenerating islet-derived 3 gamma (REG3G), which is associated with changes in the secretion of mucin-2 (Muc2). Pro-inflammatory molecules such as cytokines, interferons, and TNF may serve as early reporters of MS. Other examples of microbial enzymes and metabolites that may be used as reporters in the early detection of life-threatening diseases are reviewed.

Hepatitis B virus X protein promotes tumor glycolysis by downregulating lncRNA OIP5-AS1/HKDC1 in HCC

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related mortality worldwide, with Hepatitis B virus (HBV) infection being the leading cause. This study aims to investigate the role of HBV in HCC pathogenesis involving glucose metabolism. Long non-coding RNA (lncRNA) OIP5-AS1 was significantly downregulated in HBV-positive HCC patients, and its low expression indicated a poor prognosis. This lncRNA was primarily localized in the cytoplasm, acting as a tumor suppressor. HBV protein X (HBx) repressed OIP5-AS1 expression by inhibiting a ligand-activated transcriptional factor peroxisome proliferator-activated receptor α (PPARα). Furthermore, mechanistic studies revealed that OIP5-AS1 inhibited tumor growth by suppressing Hexokinase domain component 1 (HKDC1)-mediated glycolysis. The expression of HKDC1 could be enhanced by transcriptional factor sterol regulatory element-binding protein 1 (SREBP1). OIP5-AS1 facilitated the ubiquitination and degradation of SREBP1 to suppress HKDC1 transcription, which inhibited glycolysis. The results suggest that lncRNA OIP5-AS1 plays an anti-oncogenic role in HBV-positive HCC via the HBx/OIP5-AS1/HKDC1 axis, providing a promising diagnostic marker and therapeutic target for HBV-positive HCC patients.

Microbiome bacterial influencers of host immunity and response to immunotherapy

The gut microbiota influences anti-tumor immunity and can induce or inhibit response to immune checkpoint inhibitors (ICIs). Therefore, microbiome features are being studied as predictive/prognostic biomarkers of patient response to ICIs, and microbiome-based interventions are attractive adjuvant treatments in combination with ICIs. Specific gut-resident bacteria can influence the effectiveness of immunotherapy; however, the mechanism of action on how these bacteria affect anti-tumor immunity and response to ICIs is not fully understood. Nevertheless, early bacterial-based therapeutic strategies have demonstrated that targeting the gut microbiome through various methods can enhance the effectiveness of ICIs, resulting in improved clinical responses in patients with a diverse range of cancers. Therefore, understanding the microbiota-driven mechanisms of response to immunotherapy can augment the success of these interventions, particularly in patients with treatment-refractory cancers.

Modulating gut microbiome in cancer immunotherapy: Harnessing microbes to enhance treatment efficacy

Immunotherapy has emerged as a robust approach against cancer, yet its efficacy has varied among individuals, accompanied by the occurrence of immune-related adverse events. As a result, the efficacy of immunotherapy is far from satisfactory, and enormous efforts have been invested to develop strategies to improve patient outcomes. The gut microbiome is now well acknowledged for its critical role in immunotherapy, with better understanding on host-microbes interaction in the context of cancer treatment. Also, an increasing number of trials have been conducted to evaluate the potential and feasibility of microbiome-targeting approaches to enhance efficacy of cancer treatment in patients. Here, the role of the gut microbiome and metabolites (e.g., short-chain fatty acids, tryptophan metabolites) in immunotherapy and the underlying mechanisms are explored. The application of microbiome-targeting approaches that aim to improve immunotherapy efficacy (e.g., fecal microbiota transplantation, probiotics, dietary intervention) is also elaborated, with further discussion on current challenges and suggestions for future research.

Circulating tumour DNA-Based molecular residual disease detection in resectable cancers: a systematic review and meta-analysis

BACKGROUND

Circulating tumour DNA (ctDNA)-based molecular residual disease (MRD) detection technology has been widely used for recurrence evaluation, but there is no agreement on the efficacy of assessing recurrence and overall survival (OS) prognosis, as well as the sensitivity and specificity of landmark detection and longitudinal detection.

METHODS

We systematically searched Pubmed, Embase, Cochrane, and Scopus for prospective studies or randomized controlled trials that collected blood samples prospectively. The search period was from Jan 1, 2013, to Sept 10, 2023. We excluded retrospective studies. The primary endpoint was to assess the hazard ratio (HR) between circulating tumour DNA positive (ctDNA+) and negative (ctDNA-) for recurrence-free survival incidence (RFS), disease-free survival (DFS), progression-free survival (PFS), event-free survival (EFS), time to recurrence (TTR), distant metastasis-free survival (DMFS) or OS in patients with resectable cancers. We calculated the pooled HR of recurrence and OS and 95% confidence interval (CI) in patients with resected cancers using a random-effects model. Pooled sensitivity and specificity were estimated using the bivariate random effects model.

FINDINGS

This systematic review and meta-analysis returned 7578 records, yielding 80 included studies after exclusion. We found that the HR of recurrence across all included cancers between patients with ctDNA+ and ctDNA- was 7.48 (95% CI 6.39-8.77), and the OS was 5.58 (95% CI 4.17-7.48). We also found that the sensitivity, area under the summary receiver operating characteristic curve (AUSROC) and diagnostic odds ratio (DOR) of longitudinal tests were higher than that of landmark tests between patients with ctDNA+ and ctDNA- (0.74, 95% CI 0.68-0.80 vs 0.50, 95% CI 0.46-0.55; 0.88 vs. 0.80; 25.70, 95% CI 13.20-45.40 vs. 9.90, 95% CI 7.77-12.40).

INTERPRETATION

Postoperative ctDNA testing was a significant prognosis factor for recurrence and OS in patients with resectable cancers. However, the overall sensitivity of ctDNA-MRD detection could be better. Longitudinal monitoring can improve the sensitivity, AUSROC, and DOR.

FUNDING

Special fund project for clinical research of Qingyuan People's Hospital (QYRYCRC2023006), plan on enhancing scientific research in GMU (GZMU-SH-301).

Cancer stem cell-immune cell crosstalk in the tumor microenvironment for liver cancer progression

Crosstalk between cancer cells and the immune microenvironment is determinant for liver cancer progression. A tumor subpopulation called liver cancer stem cells (CSCs) significantly accounts for the initiation, metastasis, therapeutic resistance, and recurrence of liver cancer. Emerging evidence demonstrates that the interaction between liver CSCs and immune cells plays a crucial role in shaping an immunosuppressive microenvironment and determining immunotherapy responses. This review sheds light on the bidirectional crosstalk between liver CSCs and immune cells for liver cancer progression, as well as the underlying molecular mechanisms after presenting an overview of liver CSCs characteristic and their microenvironment. Finally, we discuss the potential application of liver CSCs-targeted immunotherapy for liver cancer treatment.

Prognostic value of CD8+T cells related genes and exhaustion regulation of Notch signaling pathway in hepatocellular carcinoma

Immunotherapy has emerged as the primary treatment modality for patients with advanced Hepatocellular carcinoma (HCC). However, its clinical efficacy remains limited, benefiting only a subset of patients, while most exhibit immune tolerance and face a grim prognosis. The infiltration of immune cells plays a pivotal role in tumor initiation and progression. In this study, we conducted an analysis of immune cell infiltration patterns in HCC patients and observed a substantial proportion of CD8+T cells. Leveraging the weighted gene co-expression network analysis (WGCNA), we identified 235 genes associated with CD8+T cell and constructed a risk prediction model. In this model, HCC patients were stratified into a high-risk and low-risk group. Patients in the high-risk group exhibited a lower survival rate, predominantly presented with intermediate to advanced stages of cancer, displayed compromised immune function, showed limited responsiveness to immunotherapy, and demonstrated elevated expression levels of the Notch signaling pathway. Further examination of clinical samples demonstrated an upregulation of the Notch1+CD8+T cell exhaustion phenotype accompanied by impaired cytotoxicity and cytokine secretion functions that worsened with increasing Notch activation levels. Our study not only presents a prognostic model but also highlights the crucial involvement of the Notch pathway in CD8+T cell exhaustion-a potential target for future immunotherapeutic interventions.

Role of immunotherapies and stem cell therapy in the management of liver cancer: A comprehensive review

Liver cancer (LC) is the sixth most common disease and the third most common cause of cancer-related mortality. The WHO predicts that more than 1 million deaths will occur from LC by 2030. Hepatocellular carcinoma (HCC) is a common form of primary LC. Today, the management of LC involves multiple disciplines, and multimodal therapy is typically selected on an individual basis, considering the intricate interactions between the patient's overall health, the stage of the tumor, and the degree of underlying liver disease. Currently, the treatment of cancers, including LC, has undergone a paradigm shift in the last ten years because of immuno-oncology. To treat HCC, immune therapy approaches have been developed to enhance or cause the body's natural immune response to specifically target tumor cells. In this context, immune checkpoint pathway inhibitors, engineered cytokines, adoptive cell therapy, immune cells modified with chimeric antigen receptors, and therapeutic cancer vaccines have advanced to clinical trials and offered new hope to cancer patients. The outcomes of these treatments are encouraging. Additionally, treatment using stem cells is a new approach for restoring deteriorated tissues because of their strong differentiation potential and capacity to release cytokines that encourage cell division and the formation of blood vessels. Although there is no proof that stem cell therapy works for many types of cancer, preclinical research on stem cells has shown promise in treating HCC. This review provides a recent update regarding the impact of immunotherapy and stem cells in HCC and promising outcomes.

Immune checkpoint inhibitors in the treatment of hepatocellular carcinoma

Despite advances in cancer treatment, hepatocellular carcinoma (HCC), the most common form of liver cancer, remains a major public health problem worldwide. The immune microenvironment plays a critical role in regulating tumor progression and resistance to therapy, and in HCC, the tumor microenvironment (TME) is characterized by an abundance of immunosuppressive cells and signals that facilitate immune evasion and metastasis. Recently, anti-cancer immunotherapies, therapeutic interventions designed to modulate the immune system to recognize and eliminate cancer, have become an important cornerstone of cancer therapy. Immunotherapy has demonstrated the ability to improve survival and provide durable cancer control in certain groups of HCC patients, while reducing adverse side effects. These findings represent a significant step toward improving cancer treatment outcomes. As demonstrated in clinical trials, the administration of immune checkpoint inhibitors (ICIs), particularly in combination with anti-angiogenic agents and tyrosine kinase inhibitors, has prolonged survival in a subset of patients with HCC, providing an alternative for patients who progress on first-line therapy. In this review, we aimed to provide an overview of HCC and the role of the immune system in its development, and to summarize the findings of clinical trials involving ICIs, either as monotherapies or in combination with other agents in the treatment of the disease. Challenges and considerations regarding the administration of ICIs in the treatment of HCC are also outlined.

Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation

Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat infiltration. These features are pivotal to measuring the state of muscle functional health and in tracking the response of the body to musculoskeletal and neuromusculoskeletal disorders. The gold standard approach to perform muscle segmentation requires manual processing of large numbers of images and is associated with significant operator repeatability issues and high time requirements. Deep learning-based techniques have been recently suggested to be capable of automating the process, which would catalyse research into the effects of musculoskeletal disorders on the muscular system. In this study, three convolutional neural networks were explored in their capacity to automatically segment twenty-three lower limb muscles from the hips, thigh, and calves from magnetic resonance images. The three neural networks (UNet, Attention UNet, and a novel Spatial Channel UNet) were trained independently with augmented images to segment 6 subjects and were able to segment the muscles with an average Relative Volume Error (RVE) between -8.6% and 2.9%, average Dice Similarity Coefficient (DSC) between 0.70 and 0.84, and average Hausdorff Distance (HD) between 12.2 and 46.5 mm, with performance dependent on both the subject and the network used. The trained convolutional neural networks designed, and data used in this study are openly available for use, either through re-training for other medical images, or application to automatically segment new T1-weighted lower limb magnetic resonance images captured with similar acquisition parameters.

Targeted immunotherapy to cancer stem cells: A novel strategy of anticancer immunotherapy

Cancer is a major disease that endangers human health. Cancer drug resistance and relapse are the two main causes contributing to cancer treatment failure. Cancer stem cells (CSCs) are a small fraction of tumor cells that are responsible for tumorigenesis, metastasis, relapse, and resistance to conventional anticancer therapies. Therefore, CSCs are considered to be the root of cancer recurrence, metastasis, and drug resistance. Novel anticancer strategies need to face this new challenge and explore their efficacy against CSCs. Recently, immunotherapy has made rapid advances in cancer treatment, and its potential against CSCs is also an interesting area of research. Meanwhile, immunotherapy strategies are novel therapeutic modalities with promising results in targeting CSCs. In this review, we summarize the targeting of CSCs by various immunotherapy strategies such as monoclonal antibodies(mAb), tumor vaccines, immune checkpoint inhibitors, and chimeric antigen receptor-T cells(CAR-T) in pre-clinical and clinical studies. This review provides new insights into the application of these immunotherapeutic approaches to potential anti-tumor therapies in the future.

Mechanisms of drug resistance in HCC

HCC comprises ∼80% of primary liver cancer. HCC is the only major cancer for which death rates have not improved over the last 10 years. Most patients are diagnosed with advanced disease when surgical and locoregional treatments are not feasible or effective. Sorafenib, a multikinase inhibitor targeting cell growth and angiogenesis, was approved for advanced unresectable HCC in 2007. Since then, other multikinase inhibitors have been approved. Lenvatinib was found to be noninferior to sorafenib as a first-line agent. Regorafenib, cabozantinib, and ramucirumab were shown to prolong survival as second-line agents. Advances in immunotherapy for HCC have also added hope for patients, but their efficacy remains limited. A large proportion of patients with advanced HCC gain no long-term benefit from systemic therapy due to primary and acquired drug resistance, which, combined with its rising incidence, keeps HCC a highly fatal disease. This review summarizes mechanisms of primary and acquired resistance to therapy and includes methods for bypassing resistance. It addresses recent advancements in immunotherapy, provides new perspectives on the linkage between drug resistance and molecular etiology of HCC, and evaluates the role of the microbiome in drug resistance. It also discusses alterations in signaling pathways, dysregulation of apoptosis, modulations in the tumor microenvironment, involvement of cancer stem cells, changes in drug metabolism/transport, tumor hypoxia, DNA repair, and the role of microRNAs in drug resistance. Understanding the interplay among these factors will provide guidance on the development of new therapeutic strategies capable of improving patient outcomes.

Tumor-associated macrophage subtypes on cancer immunity along with prognostic analysis and SPP1-mediated interactions between tumor cells and macrophages

Tumor-associated macrophages (TAM) subtypes have been shown to impact cancer prognosis and resistance to immunotherapy. However, there is still a lack of systematic investigation into their molecular characteristics and clinical relevance in different cancer types. Single-cell RNA sequencing data from three different tumor types were used to cluster and type macrophages. Functional analysis and communication of TAM subpopulations were performed by Gene Ontology-Biological Process and CellChat respectively. Differential expression of characteristic genes in subpopulations was calculated using zscore as well as edgeR and Wilcoxon rank sum tests, and subsequently gene enrichment analysis of characteristic genes and anti-PD-1 resistance was performed by the REACTOME database. We revealed the heterogeneity of TAM, and identified eleven subtypes and their impact on prognosis. These subtypes expressed different molecular functions respectively, such as being involved in T cell activation, apoptosis and differentiation, or regulating viral bioprocesses or responses to viruses. The SPP1 pathway was identified as a critical mediator of communication between TAM subpopulations, as well as between TAM and epithelial cells. Macrophages with high expression of SPP1 resulted in poorer survival. By in vitro study, we showed SPP1 mediated the interactions between TAM clusters and between TAM and tumor cells. SPP1 promoted the tumor-promoting ability of TAM, and increased PDL1 expression and stemness of tumor cells. Inhibition of SPP1 attenuated N-cadherin and β-catenin expression and the activation of AKT and STAT3 pathway in tumor cells. Additionally, we found that several subpopulations could decrease the sensitivity of anti-PD-1 therapy in melanoma. SPP1 signal was a critical pathway of communication between macrophage subtypes. Some specific macrophage subtypes were associated with immunotherapy resistance and prognosis in some cancer types.

Efficacy of immunotherapy in hepatocellular carcinoma: Does liver disease etiology have a role?

The systemic treatment of hepatocellular carcinoma (HCC) is changing rapidly. After a decade of tyrosine kinase inhibitors (TKIs), as the only therapeutic option for the treatment of advanced HCC, in the last few years several phase III trials demonstrated the efficacy of immune checkpoint inhibitors (ICIs). The combination of the anti-PD-L1 atezolizumab and the anti-vascular endothelial growth factor (VEGF) bevacizumab demonstrated the superiority over sorafenib and currently represents the standard of care treatment for advanced HCC. In addition, the combination of durvalumab (an anti-PD-L1) and tremelimumab (an anti-CTLA4) proved to be superior to sorafenib, and in the same trial durvalumab monotherapy showed non-inferiority compared to sorafenib. However, early reports suggest an influence of HCC etiology in modulating the response to these drugs. In particular, a lower effectiveness of ICIs has been suggested in patients with non-viral HCC (in particular non-alcoholic fatty liver disease). Nevertheless, randomized controlled trials available to date have not been stratified for etiology and data suggesting a possible impact of etiology in the outcome of patients managed with ICIs derive from subgroup not pre-specified analyses. In this review, we aim to examine the potential impact of HCC etiology on the response to immunotherapy regimens for HCC.

The role of bile acid receptor TGR5 in regulating inflammatory signalling

Takeda G protein-coupled receptor 5 (TGR5) is a bile acid receptor, and its role in regulating metabolism after binding with bile acids has been established. Since the immune response depends on metabolism to provide biomolecules and energy to cope with challenging conditions, emerging evidence reveals the regulatory effects of TGR5 on the immune response. An in-depth understanding of the effect of TGR5 on immune regulation can help us disentangle the interaction of metabolism and immune response, accelerating the development of TGR5 as a therapeutic target. Herein, we reviewed more than 200 articles published in the last 20 years in PubMed, to discuss the roles of TGR5 in regulating inflammatory response, the molecular mechanism, as well as existing problems. Particularly, its anti-inflammation effect is emphasized.

Three-dimensional morphology scoring of hepatocellular carcinoma stratifies prognosis and immune infiltration

BACKGROUND

The morphological attributes could serve as pivotal indicators precipitating early recurrence and dismal overall survival in hepatocellular carcinoma (HCC), and quantifying morphological features may better stratify the prognosis of HCC.

OBJECTIVE

To develop a radiomics approach based on 3D tumor morphology features for predicting the prognosis of HCC and identifying differentially expressed genes related to morphology to guide HCC treatment.

MATERIALS AND METHODS

Retrospective study of 357 HCC patients. Radiomic features were extracted from MRI tumor regions; 14 morphology-related features predicted early HCC recurrence and patient stratification via LASSO-Cox modeling. Overall survival (OS) and recurrence-free survival (RFS) were analyzed. RNA sequencing from the Cancer Imaging Archive (TCIA) examined drug sensitivity and stratified HCC using morphological immunity genes, validating recurrence and prognosis.

RESULTS

Patients were split into training (n = 225), test (n = 132), and 50 TCIA dataset cohorts. Two features (Maximum2DdiameterColumn, Sphericity) in Cox regression stratified patients into high/low-risk Morphological Radiological Score (Morph-RS) groups. Significant OS and RFS were seen across all sets. Differentially expressed genes focused on T cell receptor signaling; low-risk group had higher T cells (P = 0.039), B cells (P = 0.041), NK cells (P = 0.018). SN-38, GSK2126458 might treat high-risk morphology. Morphology-immune genes stratified HCC, showing significant RFS/OS differences.

CONCLUSION

Tumor Morph-RS effectively stratifies HCC patients' recurrence and prognosis. Limited immune infiltration seen in Morph-RS high-risk groups signifies the potential of employing tumor morphology as a potent visual biomarker for diagnosing and managing HCC.

Single-cell tracking as a tool for studying EMT-phenotypes

This article demonstrates that label-free single-cell video tracking is a useful approach for in vitro studies of Epithelial-Mesenchymal Transition (EMT). EMT is a highly heterogeneous process, involved in wound healing, embryogenesis and cancer. The process promotes metastasis, and increased understanding can aid development of novel therapeutic strategies. The role of EMT-associated biomarkers depends on biological context, making it challenging to compare and interpret data from different studies. We demonstrate single-cell video tracking for comprehensive phenotype analysis. In this study we performed single-cell video tracking on 72-h long recordings. We quantified several behaviours at a single-cell level during induced EMT in MDA-MB-468 cells. This revealed notable variations in migration speed, with different dose-response patterns and varying distributions of speed. By registering cell morphologies during the recording, we determined preferred paths of morphological transitions. We also found a clear association between migration speed and cell morphology. We found elevated rates of cell death, diminished proliferation, and an increase in mitotic failures followed by re-fusion of sister-cells. The method allows tracking of phenotypes in cell lineages, which can be particularly useful in epigenetic studies. Sister-cells were found to have significant similarities in their speeds and morphologies, illustrating the heritability of these traits.

Identification and validation of the clinical prediction model and biomarkers based on chromatin regulators in colon cancer by integrated analysis of bulk- and single-cell RNA sequencing data

Background

Chromatin regulators (CRs) are implicated in the development of cancer, but a comprehensive investigation of their role in colon adenocarcinoma (COAD) is inadequate. The purpose of this study is to find CRs that can provide recommendations for clinical diagnosis and treatment, and to explore the reasons why they serve as critical CRs.

Methods

We obtained data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Weighted Gene Co-Expression Network Analysis (WGCNA) screened tumor-associated CRs. LASSO-Cox regression was used to construct the model and to screen key CRs together with support vector machine (SVM), the univariate Cox regression. We used single-cell data to explore the expression of CRs in cells and their communication. Immune infiltration, immune checkpoints, mutation, methylation, and drug sensitivity analyses were performed. Gene expression was verified by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). Pan-cancer analysis was used to explore the importance of hub CRs.

Results

We finally obtained 32 tumor-associated CRs. The prognostic model was constructed based on RCOR2, PPARGC1A, PKM, RAC3, PHF19, MYBBP1A, ORC1, and EYA2 by the LASSO-Cox regression. Single-cell data revealed that the model was immune-related. Combined with immune infiltration analysis, immune checkpoint analysis, and tumor immune dysfunction and exclusion (TIDE) analysis, the low-score risk group had more immune cell infiltration and better immune response. Mutation and methylation analysis showed that multiple CRs may be mutated and methylated in colon cancer. Drug sensitivity analysis revealed that the low-risk group may be more sensitive to several drugs and PKM was associated with multiple drugs. Combined with machine learning, PKM is perhaps the most critical gene in CRs. Pan-cancer analysis showed that PKM plays a role in the prognosis of cancers.

Conclusions

We developed a prognostic model for COAD based on CRs. Increased expression of the core gene PKM is linked with a poor prognosis in several malignancies.

Influence of Microbiota on Tumor Immunotherapy

The role of the microbiome in immunotherapy has recently garnered substantial attention, with molecular studies and clinical trials providing emerging evidence on the pivotal influence of the microbiota in enhancing therapeutic outcomes via immune response modulation. However, the impact of microbial communities can considerably vary across individuals and different immunotherapeutic approaches, posing prominent challenges in harnessing their potential. In this comprehensive review, we outline the current research applications in tumor immunotherapy and delve into the possible mechanisms through which immune function is influenced by microbial communities in various body sites, encompassing those in the gut, extraintestinal barrier, and intratumoral environment. Furthermore, we discuss the effects of diverse microbiome-based strategies, including probiotics, prebiotics, fecal microbiota transplantation, and the targeted modulation of specific microbial taxa, and antibiotic treatments on cancer immunotherapy. All these strategies potentially have a profound impact on immunotherapy and pave the way for personalized therapeutic approaches and predictive biomarkers.

A novel molecular subtyping based on multi-omics analysis for prognosis predicting in colorectal melanoma: A 16-year prospective multicentric study

Colorectal melanoma (CRM) is a rare malignant tumor with severe complications, and there is currently a lack of systematic research. We conducted a study that combined proteomics and mutation data of CRM from a cohort of three centers over a 16-years period (2005-2021). The patients were divided into a training set consisting of two centers and a testing set comprising the other center. Unsupervised clustering was conducted on the training set to form two molecular subtypes for clinical characterization and functional analysis. The testing set was used to validate the survival differences between the two subtypes. The comprehensive analysis identified two subtypes of CRM: immune exhausted C1 cluster and DNA repair C2 cluster. The former subtype exhibited characteristics of metabolic disturbance, immune suppression, and poor prognosis, along with APC mutations. A machine learning algorithm named Support Vector Machine (SVM) was applied to predict the classification of CRM patients based on protein expression in the external testing cohort. Two subtypes of primary CRM with clinical and proteomic characteristics provides a reference for subsequent diagnosis and treatments.

Exploring the regulatory mechanism of intestinal flora based on PD-1 receptor/ligand targeted cancer immunotherapy

Serving as a pivotal immunotherapeutic approach against tumors, anti-PD-1/PD-L1 therapy amplifies the immune cells' capability to eliminate tumors by obstructing the interaction between PD-1 and PD-L1. Research indicates that immune checkpoint inhibitors are effective when a patient's gut harbors unique beneficial bacteria. As such, it has further been revealed that the gut microbiome influences tumor development and the efficacy of cancer treatments, with metabolites produced by the microbiome playing a regulatory role in the antitumor efficacy of Immune checkpoint inhibitors(ICBs). This article discusses the mechanism of anti-PD-1 immunotherapy and the role of intestinal flora in immune regulation. This review focuses on the modulation of intestinal flora in the context of PD-1 immunotherapy, which may offer a new avenue for combination therapy in tumor immunotherapy.

The Influence of Drug-Eluting Beads Transarterial Chemoembolization on Serum Levels of Soluble Programmed Cell Death Protein-1 in Advanced Hepatocellular Carcinoma Patients

Aim

This study aims to explore the role of soluble programmed cell death protein 1 (sPD-1) in individuals with hepatocellular carcinoma (HCC) undergoing treatment with drug-eluting beads transarterial chemoembolization (D-TACE). Additionally, we aim to assess the potential utility of sPD-1 for determining the optimal timing for combining D-TACE with immune checkpoint inhibitors (ICIs).

Materials and Methods

A total of 44 HCC patients eligible for D-TACE and 55 healthy volunteers were enrolled in this study. Three milliliters of peripheral venous blood from the patients were collected on the day before D-TACE and 3, 7, and 30 days after D-TACE, respectively, for the assay of sPD-1. The relationships between sPD-1 levels, clinical features, outcomes, and the fluctuation of sPD-1 during treatment were analyzed.

Results

The initial sPD-1 levels in patients were found to be significantly higher than those in the control group. Although the initial sPD-1 levels displayed a decreasing trend with an increase in BCLC stage, no significant differences were observed among patients at different BCLC stages. The sPD-1 level on day 3 after D-TACE was similar to that on day 7 after D-TACE and significantly lower than the initial level. The sPD-1 level on day 30 after D-TACE was significantly higher than that on day 3 and day 7 after D-TACE and nearly returned to the initial level before D-TACE.

Conclusion

The level of sPD-1 was found to be significantly elevated in patients with HCC. However, further research is deemed necessary to fully understand the role of sPD-1 as a potential biomarker in the initiation, progression, and prognosis of HCC. The decrease in sPD-1 following D-TACE suggests that immune effector cells might potentially be reduced, as well as immune function weakened, highlighting the need to avoid the prompt administration of ICIs after D-TACE.

Antitumour mechanisms of traditional Chinese medicine elicited by regulating tumour-associated macrophages in solid tumour microenvironments

Tumour-associated macrophages (TAMs), particularly M2-TAMs, constitute the largest proportion of immune cells in the solid tumour microenvironment, playing a crucial role in tumour progression and correlating with poor prognosis. TAMs promote the proliferation, invasion, and metastasis of tumour cells by remodelling the extracellular matrix, inhibiting immunity, promoting immune escape and tumour angiogenesis, and affecting cell metabolism. Traditional Chinese medicine (TCM) has been used clinically in China for millennia. Chinese herbs exhibit potent antitumour effects with minimal to no toxicity, substantially contributing to prolonging the lives of patients with cancer and improving their quality of life. TCM has unique advantages in improving the solid tumour microenvironment, particularly in regulating TAMs to further inhibit tumour angiogenesis, reduce drug resistance, reverse immunosuppression, and enhance antitumour immunity. This review highlights the TAM-associated mechanisms within the solid tumour microenvironment, outlines the recent advancements in TCM targeting TAMs for antitumour effects, emphasises the superiority of combining TCM with standard treatments or new nano-drug delivery systems, and evaluates the safety and efficacy of TCM combined with conventional treatments via clinical trials to provide insights and strategies for future research and clinical treatment.

PD-1 regulates ILC3-driven intestinal immunity and homeostasis

Interleukin-(IL) 22 production by intestinal group 3 innate lymphoid cells (ILC3) is critical to maintain gut homeostasis. However, IL-22 needs to be tightly controlled; reduced IL-22 expression is associated with intestinal epithelial barrier defect while its overexpression promotes tumor development. Here, using a single cell RNAseq approach, we identified a core set of genes associated with increased IL-22 production by ILC3. Among these genes, Programmed cell death 1 (PD-1), extensively studied in the context of cancer and chronic infection, was constitutively expressed on a subset of ILC3. These cells, found in the crypt of the small intestine and colon, displayed superior capacity to produce IL-22. PD-1 expression on ILC3 was dependent on the microbiota and was induced during inflammation in response to IL-23 but, conversely, was reduced in the presence of Notch ligand. PD-1+ ILC3 exhibited distinct metabolic activity with increased glycolytic, lipid and polyamine synthesis associated with augmented proliferation compared with their PD-1- counterparts. Further, PD-1+ ILC3 showed increased expression of mitochondrial antioxidant proteins which enable the cells to maintain their levels of reactive oxygen species (ROS). Loss of PD-1 signaling in ILC3 led to reduced IL-22 production in a cell intrinsic manner. During inflammation, PD-1 expression was increased on NCR- ILC3 while deficiency in PD-1 expression resulted in increased susceptibility to experimental colitis and failure to maintain gut barrier integrity. Collectively, our findings uncover a new function of the PD-1 and highlight the role of PD-1 signaling in the maintenance of gut homeostasis mediated by ILC3 in mice.

Gut and local microbiota in patients with cancer: increasing evidence and potential clinical applications

In recent years, cancer research has highlighted the role of disrupted microbiota in carcinogenesis and cancer recurrence. However, microbiota may also interfere with drug metabolism, influencing the efficacy of cancer drugs, especially immunotherapy, and modulating the onset of adverse events. Intestinal micro-organisms can be altered by external factors, such as use of antibiotics, proton pump inhibitors treatment, lifestyle and the use of prebiotics or probiotics. The aim of our review is to provide a picture of the current evidence about preclinical and clinical data of the role of gut and local microbiota in malignancies and its potential clinical role in cancer treatments. Standardization of microbiota sequencing approaches and its modulating strategies within prospective clinical trials could be intriguing for two aims: first, to provide novel potential biomarkers both for early cancer detection and for therapeutic effectiveness; second, to propose personalized and "microbiota-tailored" treatment strategies.

Biomarkers and computational models for predicting efficacy to tumor ICI immunotherapy

Numerous studies have shown that immune checkpoint inhibitor (ICI) immunotherapy has great potential as a cancer treatment, leading to significant clinical improvements in numerous cases. However, it benefits a minority of patients, underscoring the importance of discovering reliable biomarkers that can be used to screen for potential beneficiaries and ultimately reduce the risk of overtreatment. Our comprehensive review focuses on the latest advancements in predictive biomarkers for ICI therapy, particularly emphasizing those that enhance the efficacy of programmed cell death protein 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) inhibitors and cytotoxic T-lymphocyte antigen-4 (CTLA-4) inhibitors immunotherapies. We explore biomarkers derived from various sources, including tumor cells, the tumor immune microenvironment (TIME), body fluids, gut microbes, and metabolites. Among them, tumor cells-derived biomarkers include tumor mutational burden (TMB) biomarker, tumor neoantigen burden (TNB) biomarker, microsatellite instability (MSI) biomarker, PD-L1 expression biomarker, mutated gene biomarkers in pathways, and epigenetic biomarkers. TIME-derived biomarkers include immune landscape of TIME biomarkers, inhibitory checkpoints biomarkers, and immune repertoire biomarkers. We also discuss various techniques used to detect and assess these biomarkers, detailing their respective datasets, strengths, weaknesses, and evaluative metrics. Furthermore, we present a comprehensive review of computer models for predicting the response to ICI therapy. The computer models include knowledge-based mechanistic models and data-based machine learning (ML) models. Among the knowledge-based mechanistic models are pharmacokinetic/pharmacodynamic (PK/PD) models, partial differential equation (PDE) models, signal networks-based models, quantitative systems pharmacology (QSP) models, and agent-based models (ABMs). ML models include linear regression models, logistic regression models, support vector machine (SVM)/random forest/extra trees/k-nearest neighbors (KNN) models, artificial neural network (ANN) and deep learning models. Additionally, there are hybrid models of systems biology and ML. We summarized the details of these models, outlining the datasets they utilize, their evaluation methods/metrics, and their respective strengths and limitations. By summarizing the major advances in the research on predictive biomarkers and computer models for the therapeutic effect and clinical utility of tumor ICI, we aim to assist researchers in choosing appropriate biomarkers or computer models for research exploration and help clinicians conduct precision medicine by selecting the best biomarkers.

Innovative prognostic modeling in ESCC: leveraging scRNA-seq and bulk-RNA for dendritic cell heterogeneity analysis

Background

Globally, esophageal squamous cell carcinoma (ESCC) stands out as a common cancer type, characterized by its notably high rates of occurrence and mortality. Recent advancements in treatment methods, including immunotherapy, have shown promise, yet the prognosis remains poor. In the context of tumor development and treatment outcomes, the tumor microenvironment (TME), especially the function of dendritic cells (DCs), is significantly influential. Our study aims to delve deeper into the heterogeneity of DCs in ESCC using single-cell RNA sequencing (scRNA-seq) and bulk RNA analysis.

Methods

In the scRNA-seq analysis, we utilized the SCP package for result visualization and functional enrichment analysis of cell subpopulations. CellChat was employed to identify potential oncogenic mechanisms in DCs, while Monocle 2 traced the evolutionary trajectory of the three DC subtypes. CopyKAT assessed the benign or malignant nature of cells, and SCENIC conducted transcription factor regulatory network analysis, offering a preliminary exploration of DC heterogeneity. In Bulk-RNA analysis, we constructed a prognostic model for ESCC prognosis and immunotherapy response, based on DC marker genes. This model was validated through quantitative PCR (qPCR) and immunohistochemistry (IHC), confirming the gene expression levels.

Results

In this study, through intercellular communication analysis, we identified GALECTIN and MHC-I signaling pathways as potential oncogenic mechanisms within dendritic cells. We categorized DCs into three subtypes: plasmacytoid (pDC), conventional (cDC), and tolerogenic (tDC). Our findings revealed that pDCs exhibited an increased proportion of cells in the G2/M and S phases, indicating enhanced cellular activity. Pseudotime trajectory analysis demonstrated that cDCs were in early stages of differentiation, whereas tDCs were in more advanced stages, with pDCs distributed across both early and late differentiation phases. Prognostic analysis highlighted a significant correlation between pDCs and tDCs with the prognosis of ESCC (P< 0.05), while no significant correlation was observed between cDCs and ESCC prognosis (P = 0.31). The analysis of cell malignancy showed the lowest proportion of malignant cells in cDCs (17%), followed by pDCs (29%), and the highest in tDCs (48%), with these results being statistically significant (P< 0.05). We developed a robust ESCC prognostic model based on marker genes of pDCs and tDCs in the GSE53624 cohort (n = 119), which was validated in the TCGA-ESCC cohort (n = 139) and the IMvigor210 immunotherapy cohort (n = 298) (P< 0.05). Additionally, we supplemented the study with a novel nomogram that integrates clinical features and risk assessments. Finally, the expression levels of genes involved in the model were validated using qPCR (n = 8) and IHC (n = 16), thereby confirming the accuracy of our analysis.

Conclusion

This study enhances the understanding of dendritic cell heterogeneity in ESCC and its impact on patient prognosis. The insights gained from scRNA-seq and Bulk-RNA analysis contribute to the development of novel biomarkers and therapeutic targets. Our prognostic models based on DC-related gene signatures hold promise for improving ESCC patient stratification and guiding treatment decisions.

Cigarette smoking inhibits myoblast regeneration by promoting proteasomal degradation of NPAT protein and hindering cell cycle progression

Cigarette smoking (CS) causes skeletal muscle dysfunction, leading to sarcopenia and worse prognosis of patients with diverse systemic diseases. Here, we found that CS exposure prevented C2C12 myoblasts proliferation in a dose-dependent manner. Immunoblotting assays verified that CS exposure promoted the expression of cell cycle suppressor protein p21. Furthermore, CS exposure significantly inhibited replication-dependent (RD) histone transcription and caused S phase arrest in the cell cycle during C2C12 proliferation. Mechanistically, CS deregulated the expression levels of Nuclear Protein Ataxia-Telangiectasia Locus (NPAT/p220). Notably, the proteasome inhibitor MG132 was able to reverse the expression of NPAT in myoblasts, implying that the degradation of CS-mediated NPAT is proteasome-dependent. Overexpression of NPAT also rescued the defective proliferation phenotype induced by CS in C2C12 myoblasts. Taken together, we suggest that CS exposure induces NPAT degradation in C2C12 myoblasts and impairs myogenic proliferation through NPAT associated proteasomal-dependent mechanisms. As an application of the proteasome inhibitor MG132 or overexpression of NPAT could reverse the impaired proliferation of myoblasts induced by CS, the recovery of myoblast proliferation may be potential strategies to treat CS-related skeletal muscle dysfunction.

Advanced insights on tumor-associated macrophages revealed by single-cell RNA sequencing: The intratumor heterogeneity, functional phenotypes, and cellular interactions

Single-cell RNA sequencing (scRNA-seq) is an emerging technology used for cellular transcriptome analysis. The application of scRNA-seq has led to profoundly advanced oncology research, continuously optimizing novel therapeutic strategies. Intratumor heterogeneity extensively consists of all tumor components, contributing to different tumor behaviors and treatment responses. Tumor-associated macrophages (TAMs), the core immune cells linking innate and adaptive immunity, play significant roles in tumor progression and resistance to therapies. Moreover, dynamic changes occur in TAM phenotypes and functions subject to the regulation of the tumor microenvironment. The heterogeneity of TAMs corresponding to the state of the tumor microenvironment has been comprehensively recognized using scRNA-seq. Herein, we reviewed recent research and summarized variations in TAM phenotypes and functions from a developmental perspective to better understand the significance of TAMs in the tumor microenvironment.

Specific molecular weight of Lycium barbarum polysaccharide for robust breast cancer regression by repolarizing tumor-associated macrophages

The pro-tumorigenic M2-type tumor-associated macrophages (TAMs) in the immunosuppressive tumor microenvironment (TME) promote the progression, angiogenesis, and metastasis of breast cancer. The repolarization of TAMs from an M2-type toward an M1-type holds great potential for the inhibition of breast cancer. Here, we report that Lycium barbarum polysaccharides (LBPs) can significantly reconstruct the TME by modulating the function of TAMs. Specifically, we separated four distinct molecular weight segments of LBPs and compared their repolarization effects on TAMs in TME. The results showed that LBP segments within 50-100 kDa molecular weight range exhibited the prime effect on the macrophage repolarization, augmented phagocytosis effect of the repolarized macrophages on breast cancer cells, and regression of breast tumor in a tumor-bearing mouse model. In addition, RNA-sequencing confirms that this segment of LBP displays an enhanced anti-breast cancer effect through innate immune responses. This study highlights the therapeutic potential of LBP segments within the 50-100 kDa molecular weight range for macrophage repolarization, paving ways to offer new strategies for the treatment of breast cancer.

Novel Techniques and Models for Studying the Role of the Gut Microbiota in Drug Metabolism

The gut microbiota, known as the second human genome, plays a vital role in modulating drug metabolism, significantly impacting therapeutic outcomes and adverse effects. Emerging research has elucidated that the microbiota mediates a range of modifications of drugs, leading to their activation, inactivation, or even toxication. In diverse individuals, variations in the gut microbiota can result in differences in microbe-drug interactions, underscoring the importance of personalized approaches in pharmacotherapy. However, previous studies on drug metabolism in the gut microbiota have been hampered by technical limitations. Nowadays, advances in biotechnological tools, such as microbially derived metabolism screening and microbial gene editing, have provided a deeper insight into the mechanism of drug metabolism by gut microbiota, moving us toward personalized therapeutic interventions. Given this situation, our review summarizes recent advances in the study of gut-microbiota-mediated drug metabolism and showcases techniques and models developed to navigate the challenges posed by the microbial involvement in drug action. Therefore, we not only aim at understanding the complex interaction between the gut microbiota and drugs and outline the development of research techniques and models, but we also summarize the specific applications of new techniques and models in researching gut-microbiota-mediated drug metabolism, with the expectation of providing new insights on how to study drug metabolism by gut microbiota.

A gut microbial signature for combination immune checkpoint blockade across cancer types

Immune checkpoint blockade (ICB) targeting programmed cell death protein 1 (PD-1) and cytotoxic T lymphocyte protein 4 (CTLA-4) can induce remarkable, yet unpredictable, responses across a variety of cancers. Studies suggest that there is a relationship between a cancer patient's gut microbiota composition and clinical response to ICB; however, defining microbiome-based biomarkers that generalize across cohorts has been challenging. This may relate to previous efforts quantifying microbiota to species (or higher taxonomic rank) abundances, whereas microbial functions are often strain specific. Here, we performed deep shotgun metagenomic sequencing of baseline fecal samples from a unique, richly annotated phase 2 trial cohort of patients with diverse rare cancers treated with combination ICB (n = 106 discovery cohort). We demonstrate that strain-resolved microbial abundances improve machine learning predictions of ICB response and 12-month progression-free survival relative to models built using species-rank quantifications or comprehensive pretreatment clinical factors. Through a meta-analysis of gut metagenomes from a further six comparable studies (n = 364 validation cohort), we found cross-cancer (and cross-country) validity of strain-response signatures, but only when the training and test cohorts used concordant ICB regimens (anti-PD-1 monotherapy or combination anti-PD-1 plus anti-CTLA-4). This suggests that future development of gut microbiome diagnostics or therapeutics should be tailored according to ICB treatment regimen rather than according to cancer type.

Assessment of eligibility criteria in renal cell carcinoma trials evaluating systemic therapy

OBJECTIVES

To characterise the restrictiveness of eligibility criteria in contemporary renal cell carcinoma (RCC) trials, using recommendations from the American Society of Clinical Oncology (ASCO)-Friends of Cancer Research (FCR) initiative.

METHODS

vPhase I-III trials assessing systemic therapies in patients with RCC starting between 30 June 2012 and 30 June 2022 were identified. Eligibility criteria regarding brain metastases, prior or concurrent malignancies, hepatitis B virus (HBV) or hepatitis C virus (HCV) infection, and human immunodeficiency virus (HIV) infection were identified and stratified into three groups: exclusion, conditional inclusion, and not reported. Descriptive statistics were used to determine the frequency of eligibility criteria. Fisher's exact test or chi-square test were used to calculate their associations with certain trial characteristics.

RESULTS

A total of 423 RCC trials were initially identified of which 112 (26.5%) had sufficient accessible information. Exclusion of patients with HIV infection, HBV/HCV infection, brain metastases, and prior or concurrent malignancies were reported in 74.1%, 53.6%, 33.0%, and 8.0% of trials, respectively. In the context of HIV and HBV/HCV infection, patients were largely excluded from trials evaluating immunotherapy (94.4% and 77.8%, respectively). In addition, brain metastases were excluded in trials assessing targeted therapy (36.4%), combined therapy (33.3%), and immunotherapy (22.2%). Exclusion of patients with prior or concurrent malignancies was less frequently reported, accounting for 9.1%, 8.3%, and 5.6% targeted therapy, combined therapy and immunotherapy trials, respectively.

CONCLUSION

A substantial proportion of RCC trials utilise restrictive eligibility criteria, excluding patients with fairly prevalent comorbidities. Implementing the ASCO-FCR recommendations will ensure resulting data are more inclusive and aligned with patient populations in the real-world.

The global landscape of immune-derived lncRNA signature in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is a highly heterogeneous cancer. This heterogeneity has an impact on the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been found to play regulatory functions in cancer immunity. However, the global landscape of immune-derived lncRNA signatures has not yet been explored in colorectal cancer.

METHODS

In this study, we applied DESeq2 to identify differentially expressed lncRNAs in colon cancer. Next, we performed an integrative analysis to globally identify immune-driven lncRNA markers in CRC, including immune-associated pathways, tumor immunogenomic features, tumor-infiltrating immune cells, immune checkpoints, microsatellite instability (MSI) and tumor mutation burden (TMB).

RESULTS

We also identified dysregulated lncRNAs, such as LINC01354 and LINC02257, and their clinical relevance in CRC. Our findings revealed that the differentially expressed lncRNAs were closely associated with immune pathways. In addition, we found that RP11-354P11.3 and RP11-545G3.1 had the highest association with the immunogenomic signature. As a result, these signatures could serve as markers to assess immunogenomic activity in CRC. Among the immune cells, resting mast cells and M0 macrophages had the highest association with lncRNAs in CRC. The AC006129.2 gene was significantly associated with several immune checkpoints, for example, programmed cell death protein 1 (PD-1) and B and T lymphocyte attenuator (BTLA). Therefore, the AC006129.2 gene could be targeted to regulate the condition of immune cells or immune checkpoints to enhance the efficacy of immunotherapy in CRC patients. Finally, we identified 15 immune-related lncRNA-generated open reading frames (ORFs) corresponding to 15 cancer immune epitopes.

CONCLUSION

In conclusion, we provided a genome-wide immune-driven lncRNA signature for CRC that might provide new insights into clinical applications and immunotherapy.

Biomarker screening using integrated bioinformatics for the development of "normal-impaired glucose intolerance-type 2 diabetes mellitus"

Type 2 diabetes mellitus (T2DM) is a progressive disease. We utilized bioinformatics analysis and experimental research to identify biomarkers indicative of the progression of T2DM, aiming for early detection of the disease and timely clinical intervention. Integrating Mfuzz analysis with differential expression analysis, we identified 76 genes associated with the progression of T2DM, which were primarily enriched in signaling pathways such as apoptosis, p53 signaling, and necroptosis. Subsequently, using various analytical methods, including machine learning, we further narrowed down the hub genes to STK17A and CCT5. Based on the hub genes, we calculated the risk score for samples and interestingly found that the score correlated with multiple programmed cell death (PCD) pathways. Animal experiments revealed that the diabetes model exhibited higher levels of MDA and LDH, with lower expression of SOD, accompanied by islet cell apoptosis. In conclusion, our study suggests that during the progression of diabetes, STK17A and CCT5 may contribute to the advancement of the disease by regulating oxidative stress, programmed cell death pathways, and critical signaling pathways such as p53 and MAPK, thereby promoting the death of islet cells. This provides substantial evidence in support of further disease prevention and treatment strategies.

Multidimensional assessment of the biological effects of electronic cigarettes on lung bronchial epithelial cells

Cigarette smoke (CS) exposure is known to cause injury to respiratory tract epithelial cells and is a contributing factor in the development of chronic obstructive pulmonary disease and lung cancer. Electronic cigarettes (e-cigarettes) are gaining popularity as a potential substitute for conventional cigarettes due to their potential for aiding smoking cessation. However, the safety of e-cigarettes remains uncertain, and scientific evidence on this topic is still limited. In this study, we aimed to investigate the effects of CS and e-cigarette smoke (ECS) of different flavors on human lung bronchial epithelial cells. Real-time smoke exposure was carried out using an air-liquid interface system, and cell viability was assessed. RNA-Seq transcriptome analysis was performed to compare the differences between CS and ECS. The transcriptome analysis revealed a significantly higher number of differentially expressed genes in CS than in ECS. Moreover, the impact of mint-flavored e-cigarettes on cells was found to be greater than that of tobacco-flavored e-cigarettes, as evidenced by the greater number of differentially expressed genes. These findings provide a reference for future safety research on traditional cigarettes and e-cigarettes, particularly those of different flavors. The use of omics-scale methodologies has improved our ability to understand the biological effects of CS and ECS on human respiratory tract epithelial cells, which can aid in the development of novel approaches for smoking cessation and lung disease prevention.

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor microenvironment (TME) has been characterized well at single-cell resolution. However, a spatial interaction map of the CRC TME is still elusive. Here, we integrate multiomics analyses and establish a spatial interaction map to improve the prognosis, prediction, and therapeutic development for CRC. We construct a CRC immune module (CCIM) that comprises FOLR2+ macrophages, exhausted CD8+ T cells, tolerant CD8+ T cells, exhausted CD4+ T cells, and regulatory T cells. Multiplex immunohistochemistry is performed to depict the CCIM. Based on this, we utilize advanced deep learning technology to establish a spatial interaction map and predict chemotherapy response. CCIM-Net is constructed, which demonstrates good predictive performance for chemotherapy response in both the training and testing cohorts. Lastly, targeting FOLR2+ macrophage therapeutics is used to disrupt the immunosuppressive CCIM and enhance the chemotherapy response in vivo.

Neoadjuvant Immune Checkpoint Inhibitors in hepatocellular carcinoma: a meta-analysis and systematic review

Background

Neoadjuvant immunotherapy has demonstrated beneficial outcomes in various cancer types; however, standardized protocols for neoadjuvant immunotherapy in hepatocellular carcinoma (HCC) are currently lacking. This systematic review and meta-analysis aims to investigate the reliability of neoadjuvant immunotherapy's efficacy and safety in the context of HCC.

Methods

A systematic search was conducted across PubMed (MEDLINE), EMBASE, the Web of Science, the Cochrane Library, and conference proceedings to identify clinical trials involving resectable HCC and neoadjuvant immunotherapy. Single-arm meta-analyses were employed to compute odds ratios and 95% confidence intervals (CIs). Heterogeneity analysis, data quality assessment, and subgroup analyses based on the type of immunotherapy drugs and combination therapies were performed. This meta-analysis is registered in PROSPERO (identifier CRD42023474276).

Results

This meta-analysis included 255 patients from 11 studies. Among resectable HCC patients, neoadjuvant immunotherapy exhibited an overall major pathological response (MPR) rate of 0.47 (95% CI 0.31-0.70) and a pathological complete response (pCR) rate of 0.22 (95% CI 0.14-0.36). The overall objective response rate (ORR) was 0.37 (95% CI 0.20-0.69), with a grade 3-4 treatment-related adverse event (TRAE) incidence rate of 0.35 (95% CI 0.24-0.51). Furthermore, the combined surgical resection rate was 3.08 (95% CI 1.66-5.72). Subgroup analysis shows no significant differences in the efficacy and safety of different single-agent immunotherapies; the efficacy of dual ICIs (Immune Checkpoint Inhibitors) combination therapy is superior to targeted combined immunotherapy and monotherapy, while the reverse is observed in terms of safety.

Discussion

Neoadjuvant immunotherapy presents beneficial outcomes in the treatment of resectable HCC. However, large-scale, high-quality experiments are warranted in the future to provide robust data support.

Biomarkers and prognostic factors of PD-1/PD-L1 inhibitor-based therapy in patients with advanced hepatocellular carcinoma

Systemic therapies using programmed death-1 (PD-1) and programmed death ligand 1 (PD-L1) inhibitors have demonstrated commendable efficacy in some patients with advanced hepatocellular carcinoma (HCC); however, other individuals do not respond favorably. Hence, identifying the biomarkers, the prognostic factors, and their underlying mechanisms is crucial. In this review, we summarized the latest advancements in this field. Within the tumor microenvironment, PD-L1 expression is commonly utilized to predict response. Moreover, the characteristics of tumor-infiltrating lymphocytes are associated with the effectiveness of immunotherapy. Preclinical studies have identified stimulatory dendritic cells, conventional dendritic cells, and macrophages as potential biomarkers. The emergence of single-cell sequencing and spatial transcriptomics has provided invaluable insights into tumor heterogeneity through the lens of single-cell profiling and spatial distribution. With the widespread adoption of next-generation sequencing, certain genomic characteristics, including tumor mutational burden, copy number alterations, specific genes (TP53, CTNNB1, and GZMB), and signaling pathways (WNT/β-catenin) have been found to correlate with prognosis. Furthermore, clinical features such as tumor size, number, and metastasis status have demonstrated prognostic value. Notably, common indicators such as the Child-Pugh score and Eastern Cooperative Oncology Group score, which are used in patients with liver diseases, have shown potential. Similarly, commonly employed laboratory parameters such as baseline transforming growth factor beta, lactate dehydrogenase, dynamic changes in alpha-fetoprotein (AFP) and abnormal prothrombin, CRAFITY score (composed of C-reactive protein and AFP), and immune adverse events have been identified as predictive biomarkers. Novel imaging techniques such as EOB-MRI and PET/CT employing innovative tracers also have potential. Moreover, liquid biopsy has gained widespread use in biomarker studies owing to its non-invasive, convenient, and highly reproducible nature, as well as its dynamic monitoring capabilities. Research on the gut microbiome, including its composition, dynamic changes, and metabolomic analysis, has gained considerable attention. Efficient biomarker discovery relies on continuous updating of treatment strategies. Next, we summarized recent advancements in clinical research on HCC immunotherapy and provided an overview of ongoing clinical trials for contributing to the understanding and improvement of HCC immunotherapy.

Precision treatment in advanced hepatocellular carcinoma

The past decade has witnessed significant advances in the systemic treatment of advanced hepatocellular carcinoma (HCC). Nevertheless, the newly developed treatment strategies have not achieved universal success and HCC patients frequently exhibit therapeutic resistance to these therapies. Precision treatment represents a paradigm shift in cancer treatment in recent years. This approach utilizes the unique molecular characteristics of individual patient to personalize treatment modalities, aiming to maximize therapeutic efficacy while minimizing side effects. Although precision treatment has shown significant success in multiple cancer types, its application in HCC remains in its infancy. In this review, we discuss key aspects of precision treatment in HCC, including therapeutic biomarkers, molecular classifications, and the heterogeneity of the tumor microenvironment. We also propose future directions, ranging from revolutionizing current treatment methodologies to personalizing therapy through functional assays, which will accelerate the next phase of advancements in this area.

Liquid-liquid phase separation-related lncRNA prognostic signature and ZNF32-AS2 as a novel biomarker in hepatocellular carcinoma

BACKGROUND

Liquid-liquid phase separation (LLPS) enhances oncogenic signaling pathways and advances cancer progression, and has been proposed as a promising cancer biomarker and intervention target. Nevertheless, doubts remain about the prognostic importance of LLPS-related long non-coding RNAs (lncRNAs) in hepatocellular carcinoma (HCC).

METHODS

An LLPS-related lncRNA prognostic signature was generated by drivers and regulators of LLPS, and was validated in external datasets. The underlying genetic changes and functional enrichment of the signature were assessed. The drug sensitivity and response to immunotherapy were predicted in patients categorized as high-risk and low-risk. Clinical samples, phase separation agonist, and dispersant were used to identify lncRNAs with the most significant expression change. Cancer cells with ZNF32-AS2 expression regulation were subjected to colony formation assay, scratch test assay, migration and invasion assay, sorafenib resistance assay, and xenograft tumor model.

RESULTS

The signature of LLPS-related hub lncRNAs identified through Weighted Gene Co-Expression Network Analysis showed outstanding performance in training and external validation cohorts consistently, and the molecular characteristics varied between different risk groups. Potential drugs for high-risk individuals were identified, and low-risk individuals demonstrated a more favorable reaction to immunotherapy. ZNF32-AS2 showed the most significant expression change in phase separation agonist and dispersant treatment. ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells.

CONCLUSIONS

The LLPS-related lncRNA signature may help assess prognosis and predict treatment efficacy in clinical settings. LLPS-related ZNF32-AS2 promoted the proliferation, mobility, and sorafenib resistance of liver cancer cells, and may be a novel potential biomarker in hepatocellular carcinoma.

Liquid biopsy in colorectal cancer: Onward and upward

Colorectal cancer (CRC) remains a leading cause of cancer-related deaths worldwide. In recent years, liquid biopsy has emerged as one of the most interesting areas of research in oncology, leading to innovative trials and practical changes in all aspects of CRC management. RNAs and cell free DNA (cfDNA) methylation are emerging as promising biomarkers for early diagnosis. Post-surgical circulating tumour DNA (ctDNA) can aid in evaluating minimal residual disease and personalising adjuvant treatment. In rectal cancer, ctDNA could improve response assessment to neoadjuvant therapy and risk stratification, especially in the era of organ-preservation trials. In the advanced setting, ctDNA analysis offers the opportunity to monitor treatment response and identify driver and resistance mutations more comprehensively than traditional tissue analysis, providing prognostic and predictive information. The aim of this review is to provide a detailed overview of the clinical applications and future perspectives of liquid biopsy in CRC.

Unraveling the potential clinical utility of circulating tumor DNA detection in colorectal cancer-evaluation in a nationwide Danish cohort

BACKGROUND

Increasingly, circulating tumor DNA (ctDNA) is proposed as a tool for minimal residual disease (MRD) assessment. Digital PCR (dPCR) offers low analysis costs and turnaround times of less than a day, making it ripe for clinical implementation. Here, we used tumor-informed dPCR for ctDNA detection in a large colorectal cancer (CRC) cohort to evaluate the potential for post-operative risk assessment and serial monitoring, and how the metastatic site may impact ctDNA detection. Additionally, we assessed how altering the ctDNA-calling algorithm could customize performance for different clinical settings.

PATIENTS AND METHODS

Stage II-III CRC patients (N = 851) treated with a curative intent were recruited. Based on whole-exome sequencing on matched tumor and germline DNA, a mutational target was selected for dPCR analysis. Plasma samples (8 ml) were collected within 60 days after operation and-for a patient subset (n = 246)-every 3-4 months for up to 36 months. Single-target dPCR was used for ctDNA detection.

RESULTS

Both post-operative and serial ctDNA detection were prognostic of recurrence [hazard ratio (HR) = 11.3, 95% confidence interval (CI) 7.8-16.4, P < 0.001; HR = 30.7, 95% CI 20.2-46.7, P < 0.001], with a cumulative ctDNA detection rate of 87% at the end of sample collection in recurrence patients. The ctDNA growth rate was prognostic of survival (HR = 2.6, 95% CI 1.5-4.4, P = 0.001). In recurrence patients, post-operative ctDNA detection was challenging for lung metastases (4/21 detected) and peritoneal metastases (2/10 detected). By modifying the cut-off for calling a sample ctDNA positive, we were able to adjust the sensitivity and specificity of our test for different clinical contexts.

CONCLUSIONS

The presented results from 851 stage II-III CRC patients demonstrate that our personalized dPCR approach effectively detects MRD after operation and shows promise for serial ctDNA detection for recurrence surveillance. The ability to adjust sensitivity and specificity shows exciting potential to customize the ctDNA caller for specific clinical settings.