Spatial architecture of the immune microenvironment orchestrates tumor immunity and therapeutic response

Knowledge mapping of immunotherapy for breast cancer: A bibliometric analysis from 2013 to 2022

Breast cancer is the leading cause of cancer-related death among women globally. Immunotherapy has emerged as a major milestone in contemporary oncology. This study aims to conduct a bibliometric analysis in the field of immunotherapy for breast cancer, providing a comprehensive overview of the current research status, identifying trends and hotspots in research topics. We searched and retrieved data from the Web of Science Core Collection, and performed a bibliometric analysis of publications on immunotherapy for breast cancer from 2013 to 2022. Current status and hotspots were evaluated by co-occurrence analysis using VOSviewer. Evolution and bursts of knowledge base were assessed by co-citation analysis using CiteSpace. Thematic evolution by bibliometrix package was used to discover keywords trends. The attribution and collaboration of countries/regions, institutions and authors were also explored. A total of 7,975 publications were included. In co-occurrence analysis of keywords, 6 major clusters were revealed: tumor microenvironment, prognosis biomarker, immune checkpoints, novel drug delivery methods, immune cells and therapeutic approaches. The top three most frequently mentioned keywords were tumor microenvironment, triple-negative breast cancer, and programmed cell death ligand 1. The most productive country, institution and author were the USA (2926 publications), the University of Texas MD Anderson Cancer Center (219 publications), and Sherene Loi (28 publications), respectively. There has been a rapid growth in studies on immunotherapy for breast cancer worldwide. This research area has gained increasing attention from different countries and institutions. With the rising incidence of breast cancer, immunotherapy represents a research field of significant clinical value and potential.

Comprehensive pan-cancer analysis unveils the significant prognostic value and potential role in immune microenvironment modulation of TRIB3

TRIB3, a pseudokinase, was previously studied within only some specific cancer types, leaving its comprehensive functions in pan-cancer contexts largely unexplored. Here, we performed an integrated analysis of TRIB3 expression, prognosis, genetic alterations, functional enrichment and tumor immune-related characteristics in 33 cancer types. Our results showed that TRIB3 exhibits high expression levels across 24 different cancer types and correlates closely with unfavorable prognoses. Meanwhile, TRIB3 shows mutations in a wide spectrum of 22 distinct cancer types, with the predominant mutation types being missense mutations and gene amplifications, and significant changes in DNA methylation levels in 14 types of cancer. We further discovered that TRIB3 expression is significantly associated with cancer immune-related genome mutations, such as tumor mutational burden (TMB), microsatellite instability (MSI) and DNA mismatch repair (MMR), and infiltration of immunosuppressive cells, such as CD4+ Th2 cells and myeloid-derived suppressor cells (MDSCs), into the tumor microenvironment. These results indicated that the expression of TRIB3 might reshape the tumor immune microenvironment (TIME) and lead to immunosuppressive "cold" tumors. In addition, our results confirmed that the loss of function of TRIB3 inhibits cell proliferation, promotes apoptosis, and leads to significant enrichment of "hot" tumor-related immune pathways, at least in breast cancer cells, which further supports the important role of TRIB3 in cancer prognosis and TIME regulation. Together, this pan-cancer investigation provided a comprehensive understanding of the critical role of TRIB3 in human cancers, and suggested that TRIB3 might be a promising prognostic biomarker and a potential target for cancer immunotherapy.

Drug resistance and tumor immune microenvironment: An overview of current understandings (Review)

The use of antitumor drugs represents a reliable strategy for cancer therapy. Unfortunately, drug resistance has become increasingly common and contributes to tumor metastasis and local recurrence. The tumor immune microenvironment (TME) consists of immune cells, cytokines and immunomodulators, and collectively they influence the response to treatment. Epigenetic changes including DNA methylation and histone modification, as well as increased drug exportation have been reported to contribute to the development of drug resistance in cancers. In the past few years, the majority of studies on tumors have only focused on the development and progression of a tumor from a mechanistic standpoint; few studies have examined whether the changes in the TME can also affect tumor growth and drug resistance. Recently, emerging evidence have raised more concerns regarding the role of TME in the development of drug resistance. In the present review, it was discussed how the suppressive TME adapts to drug resistance characterized by the cooperation of immune cells, cytokines, immunomodulators, stromal cells and extracellular matrix. Furthermore, it was reviewed how these immunological or metabolic changes alter immuno‑surveillance and thus facilitate tumor drug resistance. In addition, potential targets present in the TME for developing novel therapeutic strategies to improve individualized therapy for cancer treatment were revealed.

Defining and modeling dynamic spatial heterogeneity within tumor microenvironments

Many solid tumors exhibit significant genetic, cellular, and biophysical heterogeneity which dynamically evolves during disease progression and after treatment. This constant flux in cell composition, phenotype, spatial relationships, and tissue properties poses significant challenges in accurately diagnosing and treating patients. Much of the complexity lies in unraveling the molecular changes in different tumor compartments, how they influence one another in space and time and where vulnerabilities exist that might be appropriate to target therapeutically. Recent advances in spatial profiling tools and technologies are enabling new insight into the underlying biology of complex tumors, creating a greater understanding of the intricate relationship between cell types, states, and the microenvironment. Here we reflect on some recent discoveries in this area, where the key knowledge and technology gaps lie, and the advancements in spatial measurements and in vitro models for the study of spatial intratumoral heterogeneity.

Advanced machine learning unveils CD8 + T cell genetic markers enhancing prognosis and immunotherapy efficacy in breast cancer

BACKGROUND

Breast cancer (BC) is the most common cancer in women and poses a significant health burden, especially in China. Despite advances in diagnosis and treatment, patient variability and limited early detection contribute to poor outcomes. This study examines the role of CD8 + T cells in the tumor microenvironment to identify new biomarkers that improve prognosis and guide treatment strategies.

METHODS

CD8 + T-cell marker genes were identified using single-cell RNA sequencing (scRNA-seq), and a CD8 + T cell-related gene prognostic signature (CTRGPS) was developed using 10 machine-learning algorithms. The model was validated across seven independent public datasets from the GEO database. Clinical features and previously published signatures were also analyzed for comparison. The clinical applications of CTRGPS in biological function, immune microenvironment, and drug selection were explored, and the role of hub genes in BC progression was further investigated.

RESULTS

We identified 71 CD8 + T cell-related genes and developed the CTRGPS, which demonstrated significant prognostic value, with higher risk scores linked to poorer overall survival (OS). The model's accuracy and robustness were confirmed through Kaplan-Meier and ROC curve analyses across multiple datasets. CTRGPS outperformed existing prognostic signatures and served as an independent prognostic factor. The role of the hub gene TTK in promoting malignant proliferation and migration of BC cells was validated.

CONCLUSION

The CTRGPS enhances early diagnosis and treatment precision in BC, improving clinical outcomes. TTK, a key gene in the signature, shows promise as a therapeutic target, supporting the CTRGPS's potential clinical utility.

A necroptosis-regulated model from single-cell analysis that predicts survival and identifies the Pivotal role of MAGEA6 in hepatocellular carcinoma

Objective

Hepatocellular carcinoma (HCC) ranks as the third leading cause of cancer-related deaths, constituting 75%-85 % of all primary liver cancers. The objective of this study was to develop a necroptosis-related gene signature using single-cell and bulk RNA sequencing to predict HCC patient prognoses.

Methods

A total of 25 key necroptosis regulators were identified from previous literature. We evaluated the necroptosis scores of different cell types using single-cell sequencing data from HCC and analyzed 168 necroptosis-related genes. The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset served as the training set for establishing a novel necroptosis-related gene risk signature, employing univariate and multivariate Cox regression analyses. Additionally, the study examined the model's relevance in immunity and immunotherapy, and predicted chemosensitivity in HCC patients based on the gene signature. The key genes were validated by the biological experiments.

Results

Compared to other cell types, hepatoma cells displayed the lowest necroptosis scores. A new six-gene necroptosis-related signature (S100A11, MAGEC2, MAGEA6, CTP2C9, SOX4, AKR1B10) was developed using the TCGA database and validated in the ICGC database. Patients in the high-risk category had poorer prognoses, with the risk score serving as an independent prognostic indicator beyond other clinical factors. These high-risk patients also exhibited greater immune infiltration but demonstrated a weaker anti-tumor response due to elevated expression of immune checkpoints. Pathways involving hypoxia, glycolysis, and P53, as well as the frequency of P53 somatic mutations, were notably heightened in the high-risk group. Additionally, the six genes in the model showed significantly different mRNA expression in hepatoma cell lines compared to normal hepatocytes, with the role of MAGEA6 in liver cancer being elucidated through critical experiments.

Conclusions

This study successfully developed a six-gene necroptosis-related signature to predict prognoses in HCC patients. It further explored the roles of necroptosis in hepatoma cells and the tumor microenvironment.

Modeling tumors as complex ecosystems

Many cancers resist therapeutic intervention. This is fundamentally related to intratumor heterogeneity: multiple cell populations, each with different phenotypic signatures, coexist within a tumor and its metastases. Like species in an ecosystem, cancer populations are intertwined in a complex network of ecological interactions. Most mathematical models of tumor ecology, however, cannot account for such phenotypic diversity or predict its consequences. Here, we propose that the generalized Lotka-Volterra model (GLV), a standard tool to describe species-rich ecological communities, provides a suitable framework to model the ecology of heterogeneous tumors. We develop a GLV model of tumor growth and discuss how its emerging properties provide a new understanding of the disease. We discuss potential extensions of the model and their application to phenotypic plasticity, cancer-immune interactions, and metastatic growth. Our work outlines a set of questions and a road map for further research in cancer ecology.

Deciphering the role of tryptophan metabolism-associated genes ECHS1 and ALDH2 in gastric cancer: implications for tumor immunity and personalized therapy

Background

Tryptophan Metabolism-associated Genes (TMGs), such as ECHS1 and ALDH2, are crucial in cancer progression through immunosuppressive mechanisms, particularly in Gastric Cancer (GC). This study explores their effects on the Tumor Microenvironment (TME). Additionally, it examines their potential as novel immunotherapy targets.

Methods

We utilized single-cell and bulk transcriptomic technologies to analyze the heterogeneity of GC. Non-negative Matrix Factorization (NMF) clustering identified key TMGs, and extensive RNA-seq analyses were performed to pinpoint prognostic genes and potential immunotherapy targets. Furthermore, through PCR analyses we found that ECHS1 and ALDH2 gene expression plays a regulatory role in the migration, invasion and inflammatory factor in AGS and SNU-1 cell lines. The interference effect of si-ECHS1 and ad-ALDH2 was validated using cell scratch assay in AGS and SNU-1 cell line.

Results

We observed a statistically significant correlation between ECHS1 and ALDH2 expression and increased TME heterogeneity. Our findings also revealed that ECHS1 down-regulation and ALDH2 up-regulation contribute to reduced TME heterogeneity, decreased inflammation, and inhibited AGS and SNU-1 tumor cells migration and proliferation. GSVA enrichment analysis highlighted the NF-kappa B(NF-κB) signaling pathway as specifically regulated by TMGs. Furthermore,ECHS1 and ALDH2 modulated CD8+ and CD4+ T cell activities, impacting GC progression. In vitro experiments further solidified our conclusions by showcasing the inhibitory effects of Si-ECHS1 and ad-ALDH2 on the invasive and proliferative capabilities of AGS and SNU-1 cells. Moreover, Si-ECHS1 and ad-ALDH2 gene expression effectively reduced the expression of inflammatory factors IL-10,IL-7,CXCL8 and IL-6, leading to a remarkable alleviation of chronic inflammation and the heterogeneous nature of the TME.

Conclusion

This research highlights the importance of ECHS1 and ALDH2 in GC progression and immune modulation, suggesting that targeted therapies focusing on these genes offer promising avenues for personalized immunotherapy in GC. These findings hold potential for improving patient survival and quality of life. Future studies on the NF-κB signaling pathway's role in this context are warranted to further elucidate the mechanisms underlying TMG-mediated immune modulation in GC.

Distinct tumor architectures and microenvironments for the initiation of breast cancer metastasis in the brain

Brain metastasis, a serious complication of cancer, hinges on the initial survival, microenvironment adaptation, and outgrowth of disseminated cancer cells. To understand the early stages of brain colonization, we investigated two prevalent sources of cerebral relapse, triple-negative (TNBC) and HER2+ (HER2BC) breast cancers. Using mouse models and human tissue samples, we found that these tumor types colonize the brain, with a preference for distinctive tumor architectures, stromal interfaces, and autocrine programs. TNBC models tend to form perivascular sheaths with diffusive contact with astrocytes and microglia. In contrast, HER2BC models tend to form compact spheroids driven by autonomous tenascin C production, segregating stromal cells to the periphery. Single-cell transcriptomics of the tumor microenvironment revealed that these architectures evoke differential Alzheimer's disease-associated microglia (DAM) responses and engagement of the GAS6 receptor AXL. The spatial features of the two modes of brain colonization have relevance for leveraging the stroma to treat brain metastasis.

The prognostic effect of infiltrating immune cells is shaped by proximal M2 macrophages in lung adenocarcinoma

The spatial arrangement of immune cells within the tumor microenvironment (TME) and their interactions play critical roles in the initiation and development of cancer. Several advanced technologies such as imaging mass cytometry (IMC) providing the immunological landscape of the TME with single-cell resolution. In this study, we develop a new method to quantify the spatial proximity between different cell types based on single-cell spatial data. Using this method on IMC data from 416 lung adenocarcinoma patients, we show that the proximity between different cell types is more correlated with patient prognosis compared to the traditional features such immune cell density and fractions. Consistent with previous reports, our results validate that proximity of T helper (Th) and B cells to cancer cells is associated with survival benefits. More importantly, we discover that the proximity of M2 macrophages to multiple immune cells is associated with poor prognosis. When Th/B cells are stratified into M2-distal and M2-proximal, the abundance of the former but not the latter category of Th/B cells is correlated with enhanced patient survival. Additionally, the abundance of M2-distal and M2-proximal cytotoxic T cells (Tc) is respectively associated with good and poor prognosis. Our results indicate that the prognostic effect of Th, Tc, and B cells in the tumor microenvironment is modulated by the nearby M2 macrophages. The proposed new method proposed can be readily applied to all single-cell spatial data for revealing functional impact of immune cell interactions.

Malic enzymes in cancer: Regulatory mechanisms, functions, and therapeutic implications

Malic enzymes (MEs) are metabolic enzymes that catalyze the oxidation of malate to pyruvate and NAD(P)H. While researchers have well established the physiological metabolic roles of MEs in organisms, recent research has revealed a link between MEs and carcinogenesis. This review collates evidence of the molecular mechanisms by which MEs promote cancer occurrence, including transcriptional regulation, post-transcriptional regulation, post-translational protein modifications, and protein-protein interactions. Additionally, we highlight the roles of MEs in reprogramming energy metabolism, suppressing senescence, and modulating the tumor immune microenvironment. We also discuss the involvement of these enzymes in mediating tumor resistance and how the development of novel small-molecule inhibitors targeting MEs might be a good therapeutic approach. Insights through this review are expected to provide a comprehensive understanding of the intricate relationship between MEs and cancer, while facilitating future research on the potential therapeutic applications of targeting MEs in cancer management.

Spatial landscapes of cancers: insights and opportunities

Solid tumours comprise many different cell types organized in spatially structured arrangements, with substantial intratumour and intertumour heterogeneity. Advances in spatial profiling technologies over the past decade hold promise to capture the complexity of these cellular architectures to build a holistic view of the intricate molecular mechanisms that shape the tumour ecosystem. Some of these mechanisms act at the cellular scale and are controlled by cell-autonomous programmes or communication between nearby cells, whereas other mechanisms result from coordinated efforts between large networks of cells and extracellular molecules organized into tissues and organs. In this Review we provide insights into the application of single-cell and spatial profiling tools, with a focus on spatially resolved transcriptomic tools developed to understand the cellular architecture of the tumour microenvironment and identify opportunities to use them to improve clinical management of cancers.

Analyzing the Spatial Distribution of Immune Cells in Lung Adenocarcinoma

(1) Background: This study investigates the tumor immune microenvironment, focusing on immune cell distribution in lung adenocarcinoma. (2) Methods: We evaluated fifty cases of lung adenocarcinoma, and suitable areas for further studies were annotated on the histological slides. Two tumor cores per case were obtained, one from the tumor's center and another from its periphery, and introduced into three paraffin receptor blocks for optimized processing efficiency. The 4-micrometer-thick tissue microarray sections were stained for H&E and for CD68, CD163, CD8, CD4, and PD-L1; (3) Results: Our investigation revealed significant correlations between PD-L1 expression in tumor cells and the presence of CD163+ macrophages, between CD4+ cells and CD8+, CD68+, and CD163+ cells, and also between CD8+ T cells and CD163+ cells. Additionally, while we observed some differences in cellular components and densities between the tumor center and periphery, these differences were not statistically significant. However, distinct correlations between PD-L1 and immune cells in these regions were identified, suggesting spatial heterogeneity in the immune landscape. (4) Conclusions: These results emphasize the intricate interactions between immune cells and tumor cells in lung adenocarcinoma. Understanding patient spatial immune profile could improve patient selection for immunotherapy, ensuring that those most likely to benefit are identified.

Establishment and verification of a TME prognosis scoring model based on the acute myeloid leukemia single-cell transcriptome

The tumor microenvironment (TME) plays an important role in the occurrence and progression of Acute Myeloid Leukemia (AML). Single-cell sequencing has enabled researchers to explore the correlation between TME subgroups and tumor prognosis, distinguish the existence of drug-resistant subgroups of tumor cells, and unravel the complexity of the AML cellular heterogeneity. We used bone marrow immune cell enrichment analysis from public databases to screen prognostic genes, construct prognostic models, and validate their prognostic significance on independent external datasets and patient samples. A total of 18,251 single cells were obtained to establish prognostic scoring models for 10 key genes including CCL5, ETLS2, and IL2RA.The AML cases were divided into two groups: high-risk and low-risk. The low-risk group exhibited a higher survival rate than the high-risk group. The areas under curves (AUC) of 1-, 3- and 5-year survival curves in the TCGA and GEO training sets were greater than 0.8 and 0.6, respectively, indicating effective prediction. The model's prognostic efficacy was confirmed across multiple validation sets. It demonstrated increased expression of ETS2, CCL5, and IL2RA in AML samples compared to controls, which was associated with decreased overall survival (OS). This prognostic scoring model based on tumor immune infiltration provides a reference for developing novel treatment strategies for recurrent/refractory AML.

Reshaping the tumor immune microenvironment to improve CAR-T cell-based cancer immunotherapy

In many hematologic malignancies, the adoptive transfer of chimeric antigen receptor (CAR) T cells has demonstrated notable success; nevertheless, further improvements are necessary to optimize treatment efficacy. Current CAR-T therapies are particularly discouraging for solid tumor treatment. The immunosuppressive microenvironment of tumors affects CAR-T cells, limiting the treatment's effectiveness and safety. Therefore, enhancing CAR-T cell infiltration capacity and resolving the immunosuppressive responses within the tumor microenvironment could boost the anti-tumor effect. Specific strategies include structurally altering CAR-T cells combined with targeted therapy, radiotherapy, or chemotherapy. Overall, monitoring the tumor microenvironment and the status of CAR-T cells is beneficial in further investigating the viability of such strategies and advancing CAR-T cell therapy.

Optimizing the spatial immune landscape of CD103+CD8+ tissue-resident memory T cells in non-small cell lung cancer by neoadjuvant chemotherapy

BACKGROUND

Neoadjuvant chemotherapy (NAC) combined with immunotherapy is increasingly used in non-small cell lung cancer (NSCLC). Tissue-resident memory T (TRM) cells are the primary subset responding to anti-cancer immunity. However, the immunomodulatory effects of NAC on TRM cells remain unknown.

METHODS

We established two NSCLC cohorts including patients undergoing upfront surgery (US) and NAC followed by surgery. Beyond the unpaired comparison between the US cohort (n = 122) and NAC cohort (n = 141) with resection samples, 58 matched pre-NAC biopsy samples were available for paired comparisons. Using multiplex immunofluorescence, we characterized TRM cells (CD103+CD8+) and four heterogeneous TRM subsets, including naive TRM1 (PD-1-Tim-3-), pre-exhausted TRM2 (PD-1+Tim-3-), TRM3 (PD-1-Tim-3+), and terminally exhausted TRM4 (PD-1+Tim-3+). Cell density, cytotoxicity, and two spatial features were defined to evaluate the effect of NAC on TRM subsets.

RESULTS

The cell densities, infiltration scores, and cancer-cell proximity scores of TRM cells, especially TRM1&2 subsets, were significantly increased after NAC and associated with better prognosis of patients. In Contrast, no significant change was observed in the TRM4 subset, which was associated with poor prognosis. Besides, the cytotoxicity of TRM subsets was unaltered after NAC. Compared with patients without major pathologic response (MPRs), patients with MPR had higher densities of TRM1&2 subsets and higher cancer-cell proximity scores of TRM2&3 subsets. Furthermore, increased density of CD31 + cancer microvessels was positively associated with both TRM and Tnon-RM cells after NAC.

CONCLUSIONS

NAC may remodel the cell density and spatial distribution of TRM subsets, which is associated with favorable therapeutic effect and prognosis in patients with NSCLC.

Lymphatic-localized Treg-mregDC crosstalk limits antigen trafficking and restrains anti-tumor immunity

The tumor microenvironment (TME) has a significant impact on tumor growth and immunotherapy efficacies. However, the precise cellular interactions and spatial organizations within the TME that drive these effects remain elusive. Using advanced multiplex imaging techniques, we have discovered that regulatory T cells (Tregs) accumulate around lymphatic vessels in the peripheral tumor stroma. This localized accumulation is facilitated by mature dendritic cells enriched in immunoregulatory molecules (mregDCs), which promote chemotaxis of Tregs, establishing a peri-lymphatic Treg-mregDC niche. Within this niche, mregDCs facilitate Treg activation, which in turn restrains the trafficking of tumor antigens to the draining mesenteric lymph nodes, thereby impeding the initiation of anti-tumor adaptive immune responses. Disrupting Treg recruitment to mregDCs inhibits tumor progression. Our study provides valuable insights into the organization of TME and how local crosstalk between lymphoid and myeloid cells suppresses anti-tumor immune responses.

The Potential of Immunotherapy for SMARCA4-Deficient Undifferentiated Uterine Sarcoma (SDUS)

(1) Background: SMARCA4-deficient undifferentiated uterine sarcoma (SDUS) is a rare and aggressive cancer that urgently requires novel therapeutic strategies. Despite the proven efficacy of immunotherapy in various cancer types, its application in SDUS remains largely unexplored. This study aims to investigate the immune microenvironment of SDUS to evaluate the feasibility of utilizing immunotherapy. (2) Methods: Multiplex immunofluorescence (mIF) was employed to examine the immune microenvironment in two cases of SDUS in comparison to other subtypes of endometrial stromal sarcomas (ESSs). This research involved a comprehensive evaluation of immune cell infiltration, cellular interactions, and spatial organization within the tumor immune microenvironment (TiME). Statistical analysis was performed to assess differences in immune cell densities and interactions between SDUS and other ESSs. (3) Results: SDUS exhibited a significantly higher density of cytotoxic T lymphocytes (CTLs), T helper (Th) cells, B cells, and macrophages compared to other ESSs. Notable cellular interactions included Th-CTL and Th-B cell interactions, which were more prominent in SDUS. The spatial analysis revealed distinct immune niches characterized by lymphocyte aggregation and a vascular-rich environment, suggesting an active and engaged immune microenvironment in SDUS. (4) Conclusions: The results suggest that SDUS exhibits a highly immunogenic TiME, characterized by substantial lymphocyte infiltration and dynamic cellular interactions. These findings highlight the potential of immunotherapy as an effective treatment approach for SDUS. However, given the small number of samples evaluated, these conclusions should be drawn with caution. This study underscores the importance of additional investigation into immune-targeted therapies for this challenging cancer subtype, with a larger sample size to validate and expand upon these preliminary findings.

Targeting anticancer immunity in melanoma tumour microenvironment: unleashing the potential of adjuvants, drugs, and phytochemicals

Melanoma poses a challenge in oncology because of its aggressive nature and limited treatment modalities. The tumour microenvironment (TME) in melanoma contains unique properties such as an immunosuppressive and high-density environment, unusual vasculature, and a high number of stromal and immunosuppressive cells. In recent years, numerous experiments have focused on boosting the immune system to effectively remove malignant cells. Adjuvants, consisting of phytochemicals, toll-like receptor (TLR) agonists, and cytokines, have shown encouraging results in triggering antitumor immunity and augmenting the therapeutic effectiveness of anticancer therapy. These adjuvants can stimulate the maturation of dendritic cells (DCs) and infiltration of cytotoxic CD8+ T lymphocytes (CTLs). Furthermore, nanocarriers can help to deliver immunomodulators and antigens directly to the tumour stroma, thereby improving their efficacy against malignant cells. The remodelling of melanoma TME utilising phytochemicals, agonists, and other adjuvants can be combined with current modalities for improving therapy outcomes. This review article explores the potential of adjuvants, drugs, and their nanoformulations in enhancing the anticancer potency of macrophages, CTLs, and natural killer (NK) cells. Additionally, the capacity of these agents to repress the function of immunosuppressive components of melanoma TME, such as immunosuppressive subsets of macrophages, stromal and myeloid cells will be discussed.

Comprehensive pancancer analysis reveals that LPCAT1 is a novel predictive biomarker for prognosis and immunotherapy response

Lysophosphatidylcholine acyltransferase 1 (LPCAT1) is a crucial enzyme involved in phospholipid metabolism and is essential for maintaining the structure and functionality of biofilms. However, a comprehensive examination of the role of LPCAT1 across various cancer types is lacking. Multiple public databases have been utilized to examine LPCAT1 expression, genetic alterations, methylation, prognosis, biological function, and its relationship with antitumor immunity in different cancer types. The function of LPCAT1 in glioma, breast cancer and liver cancer cells was further verified using in vitro experiments. Our research indicated that LPCAT1 is upregulated in various cancers and is accompanied by a wide range of amplification mutations. Higher LPCAT1 expression was associated with poorer prognosis across multiple cancers. Further in vitro experiments demonstrated that interfering with LPCAT1 expression increased apoptosis in glioma, breast cancer and liver cancer cells and concurrently suppressed their proliferation and migration. Functional enrichment analysis revealed that LPCAT1-associated genes were primarily enriched in immune and cancer progression pathways, such as the JAK/STAT, MYC, and EMT, etc. Moreover, LPCAT1 expression was closely associated with immune cell infiltration and immune checkpoint-related gene expression. Interestingly, LPCAT1 expression levels were generally higher in patients in the immunotherapy response group. The combination of LPCAT1 and PDL1 serves as an effective predictor of immunotherapy response. In conclusion, LPCAT1 is involved in immune regulation and tumor progression and holds promise as a biomarker for predicting patient outcomes and immunotherapy efficacy.

Immunosuppressive tumor microenvironment in the progression, metastasis, and therapy of hepatocellular carcinoma: from bench to bedside

Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy with high incidence, recurrence, and metastasis rates. The emergence of immunotherapy has improved the treatment of advanced HCC, but problems such as drug resistance and immune-related adverse events still exist in clinical practice. The immunosuppressive tumor microenvironment (TME) of HCC restricts the efficacy of immunotherapy and is essential for HCC progression and metastasis. Therefore, it is necessary to elucidate the mechanisms behind immunosuppressive TME to develop and apply immunotherapy. This review systematically summarizes the pathogenesis of HCC, the formation of the highly heterogeneous TME, and the mechanisms by which the immunosuppressive TME accelerates HCC progression and metastasis. We also review the status of HCC immunotherapy and further discuss the existing challenges and potential therapeutic strategies targeting immunosuppressive TME. We hope to inspire optimizing and innovating immunotherapeutic strategies by comprehensively understanding the structure and function of immunosuppressive TME in HCC.

Region-Specific CD16+ Neutrophils Promote Colorectal Cancer Progression by Inhibiting Natural Killer Cells

The colon is the largest compartment of the immune system, with innate immune cells exposed to antigens in the environment. However, the mechanisms by which the innate immune system is instigated are poorly defined in colorectal cancer (CRC). Here, a population of CD16+ neutrophils that specifically accumulate in CRC tumor tissues by imaging mass cytometry (IMC), immune fluorescence, and flow cytometry, which demonstrated pro-tumor activity by disturbing natural killer (NK) cells are identified. It is found that these CD16+ neutrophils possess abnormal cholesterol accumulation due to activation of the CD16/TAK1/NF-κB axis, which upregulates scavenger receptors for cholesterol intake including CD36 and LRP1. Consequently, these region-specific CD16+ neutrophils not only competitively inhibit cholesterol intake of NK cells, which interrupts NK lipid raft formation and blocks their antitumor signaling but also release neutrophil extracellular traps (NETs) to induce the death of NK cells. Furthermore, CD16-knockout reverses the pro-tumor activity of neutrophils and restored NK cell cytotoxicity. Collectively, the findings suggest that CRC region-specific CD16+ neutrophils can be a diagnostic marker and potential therapeutic target for CRC.

The YTH domain-containing protein family: Emerging players in immunomodulation and tumour immunotherapy targets

BACKGROUND

The modification of N6-methyladenosine (m6A) plays a pivotal role in tumor by altering both innate and adaptive immune systems through various pathways, including the regulation of messenger RNA. The YTH domain protein family, acting as "readers" of m6A modifications, affects RNA splicing, stability, and immunogenicity, thereby playing essential roles in immune regulation and antitumor immunity. Despite their significance, the impact of the YTH domain protein family on tumor initiation and progression, as well as their involvement in tumor immune regulation and therapy, remains underexplored and lacks comprehensive review.

CONCLUSION

This review introduces the molecular characteristics of the YTH domain protein family and their physiological and pathological roles in biological behavior, emphasizing their mechanisms in regulating immune responses and antitumor immunity. Additionally, the review discusses the roles of the YTH domain protein family in immune-related diseases and tumor resistance, highlighting that abnormal expression or dysfunction of YTH proteins is closely linked to tumor resistance.

KEY POINTS

This review provides an in-depth understanding of the YTH domain protein family in immune regulation and antitumor immunity, suggesting new strategies and directions for immunotherapy of related diseases. These insights not only deepen our comprehension of m6A modifications and YTH protein functions but also pave the way for future research and clinical applications.

The roles of tertiary lymphoid structures in genitourinary cancers: molecular mechanisms, therapeutic strategies, and clinical applications

The presence of tertiary lymphoid structures (TLSs) associated with distinct treatment efficacy and clinical prognosis has been identified in various cancer types. However, the mechanistic roles and clinical implications of TLSs in genitourinary (GU) cancers remain incompletely explored. Despite their potential role as predictive markers described in numerous studies, it is essential to comprehensively evaluate the characteristics of TLSs, including drivers of formation, structural foundation, cellular compositions, maturation stages, molecular features, and specific functionality to maximize their positive impacts on tumor-specific immunity. The unique contributions of these structures to cancer progression and biology have fueled interest in these structures as mediators of antitumor immunity. Emerging data are trying to explore the effects of therapeutic interventions targeting TLSs. Therefore, a better understanding of the molecular and phenotypic heterogeneity of TLSs may facilitate the development of TLSs-targeting therapeutic strategies to obtain optimal clinical benefits for GU cancers in the setting of immunotherapy. In this review, the authors focus on the phenotypic and functional heterogeneity of TLSs in cancer progression, current therapeutic interventions targeting TLSs and the clinical implications and therapeutic potential of TLSs in GU cancers.

lncRNA signature mediates mitochondrial permeability transition-driven necrosis in regulating the tumor immune microenvironment of cervical cancer

Mitochondrial permeability transition (MPT)-driven necrosis (MPTDN) was a regulated variant of cell death triggered by specific stimuli. It played a crucial role in the development of organisms and the pathogenesis of diseases, and may provide new strategies for treating various diseases. However, there was limited research on the mechanisms of MPTDN in cervical cancer (CESC) at present. In this study, Weighted Gene Co-expression Network Analysis (WGCNA) was performed on differentially expressed genes in CESC. The module MEyellow, which showed the highest correlation with the phenotype, was selected for in-depth analysis. It was found that the genes in the MEyellow module may be associated with the tumor immune microenvironment (TIME). Through COX univariate regression and LASSO regression analysis, 6 key genes were identified. These genes were further investigated from multiple perspectives, including their independent diagnostic value, prognostic value, specific regulatory mechanisms in the tumor immune microenvironment, drug sensitivity analysis, and somatic mutation analysis. This study provided a comprehensive exploration of the mechanisms of action of these 6 key genes in CESC patients. And qRT-PCR validation was also conducted. Through COX univariate regression and LASSO coefficient screening of the MEyellow module, 6 key genes were identified: CHRM3-AS2, AC096734.1, BISPR, LINC02446, LINC00944, and DGUOK-AS1. Evaluation of the independent diagnostic value of these 6 key genes revealed that they can serve as independent diagnostic biomarkers. Through correlation analysis among these 6 genes, a potential regulatory mechanism among them was identified. Therefore, a risk prognostic model was established based on the collective action of these 6 genes, and the model showed good performance in predicting the survival period of CESC patients. By studying the relationship between these 6 key genes and the tumor microenvironment of CESC patients from multiple angles, it was found that these 6 genes are key regulatory factors in the tumor immune microenvironment of CESC patients. Additionally, 16 drugs that are associated with these 6 key genes were identified, and 8 small molecule drugs were predicted based on the lncRNA-mRNA network. The 6 key genes can serve as independent biomarkers for diagnosis, and the Risk score of these genes when acting together can be used as an indicator for predicting the clinical survival period of CESC patients. Additionally, these 6 key genes were closely related to the tumor immune microenvironment of CESC patients and were the important regulatory factors in the tumor immune microenvironment of CESC patients.

CAR-T lymphocyte-based cell therapies; mechanistic substantiation, applications and biosafety enhancement with suicide genes: new opportunities to melt side effects

Immunotherapy has made significant strides in cancer treatment with strategies like checkpoint blockade antibodies and adoptive T cell transfer. Chimeric antigen receptor T cells (CAR-T) have emerged as a promising approach to combine these strategies and overcome their limitations. This review explores CAR-T cells as a living drug for cancer treatment. CAR-T cells are genetically engineered immune cells designed to target and eliminate tumor cells by recognizing specific antigens. The study involves a comprehensive literature review on CAR-T cell technology, covering structure optimization, generations, manufacturing processes, and gene therapy strategies. It examines CAR-T therapy in haematologic cancers and solid tumors, highlighting challenges and proposing a suicide gene-based mechanism to enhance safety. The results show significant advancements in CAR-T technology, particularly in structure optimization and generation. The manufacturing process has improved for broader clinical application. However, a series of inherent challenges and side effects still need to be addressed. In conclusion, CAR-T cells hold great promise for cancer treatment, but ongoing research is crucial to improve efficacy and safety for oncology patients. The proposed suicide gene-based mechanism offers a potential solution to mitigate side effects including cytokine release syndrome (the most common toxic side effect of CAR-T therapy) and the associated neurotoxicity.

A-to-I RNA co-editing predicts clinical outcomes and is associated with immune cells infiltration in hepatocellular carcinoma

Aberrant RNA editing has emerged as a pivotal factor in the pathogenesis of hepatocellular carcinoma (HCC), but the impact of RNA co-editing within HCC remains underexplored. We used a multi-step algorithm to construct an RNA co-editing network in HCC, and found that HCC-related RNA editings are predominantly centralized within the network. Furthermore, five pairs of risk RNA co-editing events were significantly correlated with the overall survival in HCC. Based on presence of risk RNA co-editings resulted in the categorization of HCC patients into high-risk and low-risk groups. Disparities in immune cell infiltrations were observed between the two groups, with the high-risk group exhibiting a greater abundance of exhausted T cells. Additionally, seven genes associated with risk RNA co-editing pairs were identified, whose expression effectively differentiates HCC tumor samples from normal ones. Our research offers an innovative perspective on the etiology and potential therapeutics for HCC.

Association between lymphocyte-to-monocyte ratio and prostate cancer in men: A population-based study

Using the novel inflammatory biomarker lymphocyte-to-monocyte ratio (LMR), this work aimed to look into any potential connections between LMR and prostate cancer (PCa). A cross-sectional research investigation was conducted on 7706 male participants involved in the National Health and Nutrition Examination Survey from 2001 to 2010. Multivariate logistic regression modeling investigated the relationship between LMR levels and PCa risk. Furthermore, threshold analysis, subgroup analysis, interaction testing, and smoothed curve fitting were carried out. A significant negative correlation was seen between LMR and PCa risk (OR = 0.79, 95% CI: 0.65-0.97, P = .0002), even after controlling for potential confounding factors. A significant nonlinear negative correlation with a threshold effect and a breakpoint of 4.86 was found by smooth curve fitting between LMR and PCa. Subgroup analysis revealed a significant interaction (P for interaction = 0.0448) between the negative correlation between PCa and LMR about hypertension. Moreover, additional stratified smoothed curve fitting demonstrated a statistically significant inverse relationship between PCa risk and LMR. According to our findings, there is a substantial inverse relationship between PCa risk and LMR level. The inflammatory response-related index is quick, easy to use, and offers some clinical references. However, more extensive prospective investigations are required to confirm the involvement of LMR levels in PCa.

Revisiting the role of mesenchymal stromal cells in cancer initiation, metastasis and immunosuppression

Immune checkpoint blockade (ICB) necessitates a thorough understanding of intricate cellular interactions within the tumor microenvironment (TME). Mesenchymal stromal cells (MSCs) play a pivotal role in cancer generation, progression, and immunosuppressive tumor microenvironment. Within the TME, MSCs encompass both resident and circulating counterparts that dynamically communicate and actively participate in TME immunosurveillance and response to ICB. This review aims to reevaluate various facets of MSCs, including their potential self-transformation to function as cancer-initiating cells and contributions to the creation of a conducive environment for tumor proliferation and metastasis. Additionally, we explore the immune regulatory functions of tumor-associated MSCs (TA-MSCs) and MSC-derived extracellular vesicles (MSC-EVs) with analysis of potential connections between circulating and tissue-resident MSCs. A comprehensive understanding of the dynamics of MSC-immune cell communication and the heterogeneous cargo of tumor-educated versus naïve MSCs may unveil a new MSC-mediated immunosuppressive pathway that can be targeted to enhance cancer control by ICB.

Meaningful nomograms based on systemic immune inflammation index predicted survival in metastatic pancreatic cancer patients receiving chemotherapy

OBJECTIVE

The purpose of the study is to construct meaningful nomogram models according to the independent prognostic factor for metastatic pancreatic cancer receiving chemotherapy.

METHODS

This study is retrospective and consecutively included 143 patients from January 2013 to June 2021. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) is utilized to determine the optimal cut-off value. The Kaplan-Meier survival analysis, univariate and multivariable Cox regression analysis are exploited to identify the correlation of inflammatory biomarkers and clinicopathological features with survival. R software are run to construct nomograms based on independent risk factors to visualize survival. Nomogram model is examined using calibration curve and decision curve analysis (DCA).

RESULTS

The best cut-off values of 966.71, 0.257, and 2.54 for the systemic immunological inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), and neutrophil-to-lymphocyte ratio (NLR) were obtained by ROC analysis. Cox proportional-hazards model revealed that baseline SII, history of drinking and metastasis sites were independent prognostic indices for survival. We established prognostic nomograms for primary endpoints of this study. The nomograms' predictive potential and clinical efficacy have been evaluated by calibration curves and DCA.

CONCLUSION

We constructed nomograms based on independent prognostic factors, these models have promising applications in clinical practice to assist clinicians in personalizing the management of patients.

Impact and potential value of immunosenescence on solid gastrointestinal tumors

Solid gastrointestinal tumors often respond poorly to immunotherapy for the complex tumor microenvironment (TME), which is exacerbated by immune system alterations. Immunosenescence is the process of increased diversification of immune genes due to aging and other factors, leading to a decrease in the recognition function of the immune system. This process involves immune organs, immune cells, and the senescence-associated secretory phenotype (SASP). The most fundamental change is DNA damage, resulting in TME remodeling. The main manifestations are worsening inflammation, increased immunosuppressive SASP production, decreased immune cell antitumor activity, and the accumulation of tumor-associated fibroblasts and myeloid-derived suppressor cells, making antitumor therapy less effective. Senotherapy strategies to remove senescent cells and block key senescence processes can have synergistic effects with other treatments. This review focuses on immunoenescence and its impact on the solid TME. We characterize the immunosenescent TME and discuss future directions for antitumor therapies targeting senescence.

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Research progress on the application of organoids in gynecological tumors

Organoids are in vitro 3D models that maintain their own tissue structure and function. They largely overcome the limitations of traditional tumor models and have become a powerful research tool in the field of oncology in recent years. Gynecological malignancies are major diseases that seriously threaten the life and health of women and urgently require the establishment of models with a high degree of similarity to human tumors for clinical studies to formulate individualized treatments. Currently, organoids are widely studied in exploring the mechanisms of gynecological tumor development as a means of drug screening and individualized medicine. Ovarian, endometrial, and cervical cancers as common gynecological malignancies have high morbidity and mortality rates among other gynecological tumors. Therefore, this study reviews the application of modelling, drug efficacy assessment, and drug response prediction for ovarian, endometrial, and cervical cancers, thereby clarifying the mechanisms of tumorigenesis and development, and providing precise treatment options for gynecological oncology patients.

Protocol to detect immune levels, abnormal metabolism, and signaling pathways in tumor tissue based on scRNA-seq obtained from patient databases

Malignant tumor cells are typically more active in terms of metabolism and signal transduction compared to immune and normal cells. Here, we present a protocol to evaluate immune levels, abnormal metabolism, and signaling pathways in tumor tissue based on single-cell sequencing based on patient data obtained from the GEO database. We describe steps for tumor immune microenvironment (TIME)-based evaluation, tumor purity assessment, and identification of abnormal signal transduction and metabolic pathways. We then detail procedures for screening hub genes. For complete details on the use and execution of this protocol, please refer to Bai et al.1.

The role of RNA methylation in tumor immunity and its potential in immunotherapy

RNA methylation, a prevalent post-transcriptional modification, has garnered considerable attention in research circles. It exerts regulatory control over diverse biological functions by modulating RNA splicing, translation, transport, and stability. Notably, studies have illuminated the substantial impact of RNA methylation on tumor immunity. The primary types of RNA methylation encompass N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G), and 3-methylcytidine (m3C). Compelling evidence underscores the involvement of RNA methylation in regulating the tumor microenvironment (TME). By affecting RNA translation and stability through the "writers", "erasers" and "readers", RNA methylation exerts influence over the dysregulation of immune cells and immune factors. Consequently, RNA methylation plays a pivotal role in modulating tumor immunity and mediating various biological behaviors, encompassing proliferation, invasion, metastasis, etc. In this review, we discussed the mechanisms and functions of several RNA methylations, providing a comprehensive overview of their biological roles and underlying mechanisms within the tumor microenvironment and among immunocytes. By exploring how these RNA modifications mediate tumor immune evasion, we also examine their potential applications in immunotherapy. This review aims to provide novel insights and strategies for identifying novel targets in RNA methylation and advancing cancer immunotherapy efficacy.

Establishment and validation of a novel CD8+ T cell-associated prognostic signature for predicting clinical outcomes and immunotherapy response in hepatocellular carcinoma via integrating single-cell RNA-seq and bulk RNA-seq

CD8+ T lymphocytes are critical in the immune response against neoplasms, yet the prognostic relevance of CD8+ T cell-associated genes in hepatocellular carcinoma (HCC) is not fully understood. We sourced single-cell RNA-sequencing (scRNA-seq) and bulk RNA-seq data for HCC from the GSE98638 dataset and The Cancer Genome Atlas (TCGA) repository. We utilized Weighted Gene Correlation Network Analysis (WGCNA) to identify CD8+ T cell-related genes. A clinical prognostic model for risk stratification was then constructed via Cox-Lasso regression analysis. The Immunophenotypic Score (IPS) was utilized to evaluate the potential of immunotherapeutic interventions in the categorized cohorts. Validation of the expression of CD8+ T cell-associated risk genes was performed using quantitative reverse transcription PCR (qRT-PCR). Integrating scRNA-seq with RNA-seq data, we identified five CD8+ T cell-related signature genes: IKBKE, ATP1B3, MSC, ADA, and BATF. Notably, HCC patients in the high-risk group had markedly decreased overall survival. Elevated infiltration levels of CD8+ T cells, B cells, and macrophages were observed in the high-risk group. Moreover, there was a positive correlation between the risk score and immune checkpoints (ICPs), including PDCD1, CD274, and CTLA4. Patients within the high-risk group subject to PD1 and CTLA4 blockade exhibited higher IPS levels. Additionally, the expression of the five risk genes was upregulated in HCC cell lines and tissues compared to normal cells and tissues. Our findings establish a prognostic signature based on CD8+ T cells, offering a potent predictive model for clinical outcomes and responsiveness to immunotherapy in HCC patients.

Machine learning integrative approaches to advance computational immunology

The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond traditional protein marker identification to encompass a more detailed view of cellular phenotypes and their functional roles. Recent technological advancements allow the simultaneous measurements of multiple cellular components-transcriptome, proteome, chromatin, epigenetic modifications and metabolites-within single cells, including in spatial contexts within tissues. This has led to the generation of complex multiscale datasets that can include multimodal measurements from the same cells or a mix of paired and unpaired modalities. Modern machine learning (ML) techniques allow for the integration of multiple "omics" data without the need for extensive independent modelling of each modality. This review focuses on recent advancements in ML integrative approaches applied to immunological studies. We highlight the importance of these methods in creating a unified representation of multiscale data collections, particularly for single-cell and spatial profiling technologies. Finally, we discuss the challenges of these holistic approaches and how they will be instrumental in the development of a common coordinate framework for multiscale studies, thereby accelerating research and enabling discoveries in the computational immunology field.

Computed tomography characteristics of cN0 primary non-small cell lung cancer predict occult lymph node metastasis

RATIONALE

Occult lymph node metastasis (OLNM) is frequently found in patients with resectable non-small cell lung cancer (NSCLC), despite using diagnostic methods recommended by guidelines.

OBJECTIVES

To evaluate the risk of OLNM in NSCLC patients using the radiologic characteristics of the primary tumor on computed tomography (CT).

METHODS

We retrospectively reviewed clinicopathologic features of 2042 clinical T1-4N0 NSCLC patients undergoing curative intent pulmonary resection. Unique radiological features (i.e., air-bronchogram throughout the whole tumor, heterogeneous ground-glass opacity (GGO), mainly cystic appearance, endobronchial location), percentage of solid portion, and shape of tumor margin were analyzed via a stepwise approach. We used multivariable logistic regression to assess the relationship between OLNM and tumor characteristics.

RESULTS

Compared with the other unique features, endobronchial tumors were associated with the highest risk of OLNM (OR = 3.9, 95% confidence interval (CI) = 2.29-6.62), and heterogeneous GGO and mainly cystic tumors were associated with a low risk of OLNM. For tumors without unique features, the percentage of the solid portion was measured, and solid tumors were associated with OLNM (OR = 2.49, 95% CI = 1.86-3.35). Among part-solid tumors with solid proportion > 50%, spiculated margin, and peri-tumoral GGO were associated with OLNM.

CONCLUSIONS

The risk of OLNM could be assessed using radiologic characteristics on CT. This could allow us to adequately select optimal candidates for invasive nodal staging procedures (INSPs) and complete systematic lymph node dissection.

CLINICAL RELEVANCE STATEMENT

These data may be helpful for clinicians to select appropriate candidates for INSPs and complete surgical systematic lymph node dissection in NSCLC patients.

KEY POINTS

Lymph node metastasis status plays a key role in both prognostication and treatment planning. Solid tumors, particularly endobronchial tumors, were associated with occult lymph node metastasis (OLNM). The risk of OLNM can be assessed using radiologic characteristics acquired from CT images.

Exploring tumor organoids for cancer treatment

As a life-threatening chronic disease, cancer is characterized by tumor heterogeneity. This heterogeneity is associated with factors that lead to treatment failure and poor prognosis, including drug resistance, relapse, and metastasis. Therefore, precision medicine urgently needs personalized tumor models that accurately reflect the tumor heterogeneity. Currently, tumor organoid technologies are used to generate in vitro 3D tissues, which have been shown to precisely recapitulate structure, tumor microenvironment, expression profiles, functions, molecular signatures, and genomic alterations in primary tumors. Tumor organoid models are important for identifying potential therapeutic targets, characterizing the effects of anticancer drugs, and exploring novel diagnostic and therapeutic options. In this review, we describe how tumor organoids can be cultured and summarize how researchers can use them as an excellent tool for exploring cancer therapies. In addition, we discuss tumor organoids that have been applied in cancer therapy research and highlight the potential of tumor organoids to guide preclinical research.

Immune-related signature identifies IL1R2 as an immunological and prognostic biomarker in pancreatic cancer

Objective

Pancreatic cancer is one of the most aggressive malignancies, a robust prognostic signature and novel biomarkers are urgently needed for accurate stratification of the patients and optimization of clinical decision-making.

Methods

A list of bioinformatic analysis were applied in public dataset to construct an immune-related signature. Furthermore, the most pivotal gene in the signature was identified. The potential mechanism of the core gene function was revealed through GSEA, CIBERSORT, ESTIMATE, immunophenoscore (IPS) algorithm, single-cell analysis, and functional experiment.

Results

An immune-related prognostic signature and associated nomogram were constructed and validated. Among the genes constituting the signature, interleukin 1 receptor type II (IL1R2) was identified as the gene occupying the most paramount position in the risk signature. Meanwhile, knockdown of IL1R2 significantly inhibited the proliferation, invasion, and migration ability of pancreatic cancer cells. Additionally, high IL1R2 expression was associated with reduced CD8+ T cell infiltration in pancreatic cancer microenvironment, which may be due to high programmed cell death-ligand-1 (PD-L1) expression in cancer cells. Finally, the IPS algorithm proved that patients with high IL1R2 expression possessed a higher tumor mutation burden and a higher probability of benefiting from immunotherapy.

Conclusion

In conclusion, our study constructed an efficient immune-related prognostic signature and identified the key role of IL1R2 in the development of pancreatic cancer, as well as its potential to serve as a biomarker for immunotherapy efficacy prediction for pancreatic cancer.

Notch signaling pathway in cancer: from mechanistic insights to targeted therapies

Notch signaling, renowned for its role in regulating cell fate, organ development, and tissue homeostasis across metazoans, is highly conserved throughout evolution. The Notch receptor and its ligands are transmembrane proteins containing epidermal growth factor-like repeat sequences, typically necessitating receptor-ligand interaction to initiate classical Notch signaling transduction. Accumulating evidence indicates that the Notch signaling pathway serves as both an oncogenic factor and a tumor suppressor in various cancer types. Dysregulation of this pathway promotes epithelial-mesenchymal transition and angiogenesis in malignancies, closely linked to cancer proliferation, invasion, and metastasis. Furthermore, the Notch signaling pathway contributes to maintaining stem-like properties in cancer cells, thereby enhancing cancer invasiveness. The regulatory role of the Notch signaling pathway in cancer metabolic reprogramming and the tumor microenvironment suggests its pivotal involvement in balancing oncogenic and tumor suppressive effects. Moreover, the Notch signaling pathway is implicated in conferring chemoresistance to tumor cells. Therefore, a comprehensive understanding of these biological processes is crucial for developing innovative therapeutic strategies targeting Notch signaling. This review focuses on the research progress of the Notch signaling pathway in cancers, providing in-depth insights into the potential mechanisms of Notch signaling regulation in the occurrence and progression of cancer. Additionally, the review summarizes pharmaceutical clinical trials targeting Notch signaling for cancer therapy, aiming to offer new insights into therapeutic strategies for human malignancies.

MUSTANG: Multi-sample spatial transcriptomics data analysis with cross-sample transcriptional similarity guidance

Spatially resolved transcriptomics has revolutionized genome-scale transcriptomic profiling by providing high-resolution characterization of transcriptional patterns. Here, we present our spatial transcriptomics analysis framework, MUSTANG (MUlti-sample Spatial Transcriptomics data ANalysis with cross-sample transcriptional similarity Guidance), which is capable of performing multi-sample spatial transcriptomics spot cellular deconvolution by allowing both cross-sample expression-based similarity information sharing as well as spatial correlation in gene expression patterns within samples. Experiments on a semi-synthetic spatial transcriptomics dataset and three real-world spatial transcriptomics datasets demonstrate the effectiveness of MUSTANG in revealing biological insights inherent in the cellular characterization of tissue samples under study.

VOLTA: an enVironment-aware cOntrastive ceLl represenTation leArning for histopathology

In clinical oncology, many diagnostic tasks rely on the identification of cells in histopathology images. While supervised machine learning techniques necessitate the need for labels, providing manual cell annotations is time-consuming. In this paper, we propose a self-supervised framework (enVironment-aware cOntrastive cell represenTation learning: VOLTA) for cell representation learning in histopathology images using a technique that accounts for the cell's mutual relationship with its environment. We subject our model to extensive experiments on data collected from multiple institutions comprising over 800,000 cells and six cancer types. To showcase the potential of our proposed framework, we apply VOLTA to ovarian and endometrial cancers and demonstrate that our cell representations can be utilized to identify the known histotypes of ovarian cancer and provide insights that link histopathology and molecular subtypes of endometrial cancer. Unlike supervised models, we provide a framework that can empower discoveries without any annotation data, even in situations where sample sizes are limited.

Cancer-associated fibroblast-derived gene signature discriminates distinct prognoses by integrated single-cell and bulk RNA-seq analyses in breast cancer

BACKGROUND

Cancer-associated fibroblasts (CAFs) are one of the most predominant cellular subpopulations in the tumor stroma and play an integral role in cancer occurrence and progression. However, the prognostic role of CAFs in breast cancer remains poorly understood.

METHODS

We identified a number of CAF-related biomarkers in breast cancer by combining single-cell and bulk RNA-seq analyses. Based on univariate Cox regression as well as Least Absolute Shrinkage and Selection Operator (LASSO) regression analysis, a novel CAF-associated prognostic model was developed. Breast cancer patients were grouped according to the median risk score and further analyzed for outcome, clinical characteristic, pathway activity, genomic feature, immune landscape, and drug sensitivity.

RESULTS

A total of 341 CAF-related biomarkers were identified from single-cell and bulk RNA-seq analyses. We eventually screened eight candidate prognostic genes, including CERCAM, EMP1, SDC1, PRKG1, XG, TNN, WLS, and PDLIM4, and constructed the novel CAF-related prognostic model. Grouped by the median risk score, high-risk patients showed a significantly worse prognosis and exhibited distinct pathway activities such as uncontrolled cell cycle progression, angiogenesis, and activation of glycolysis. In addition, the combined risk score and tumor mutation burden significantly improved the ability to predict patient prognosis. Importantly, patients in the high-risk group had a higher infiltration of M2 macrophages and a lower infiltration of CD8+ T cells and activated NK cells. Finally, we calculated the IC50 for a range of anticancer drugs and personalized the treatment regimen for each patient.

CONCLUSION

Integrating single-cell and bulk RNA-seq analyses, we identified a list of compositive CAF-associated biomarkers and developed a novel CAF-related prognostic model for breast cancer. This robust CAF-derived gene signature acts as an excellent predictor of patient outcomes and treatment responses in breast cancer.

The impact of the P2X7 receptor on the tumor immune microenvironment and its effects on tumor progression

Cancer is a significant global health concern, and finding effective methods to treat it has been a focus of scientific research. It has been discovered that the growth, invasion, and metastasis of tumors are closely related to the environment in which they exist, known as the tumor microenvironment (TME). The immune response interacting with the tumor occurring within the TME constitutes the tumor immune microenvironment, and the immune response can lead to anti-tumor and pro-tumor outcomes and has shown tremendous potential in immunotherapy. A channel called the P2X7 receptor (P2X7R) has been identified within the TME. It is an ion channel present in various immune cells and tumor cells, and its activation can lead to inflammation, immune responses, angiogenesis, immunogenic cell death, and promotion of tumor development. This article provides an overview of the structure, function, and pharmacological characteristics of P2X7R. We described the concept and components of tumor immune microenvironment and the influence immune components has on tumors. We also outlined the impact of P2X7R regulation and how it affects the development of tumors and summarized the effects of drugs targeting P2X7R on tumor progression, both past and current, assisting researchers in treating tumors using P2X7R as a target.

DDR1-targeted therapies: current limitations and future potential

Discoidin domain receptor (DDR)-1 has a crucial role in regulating vital processes, including cell differentiation, proliferation, adhesion, migration, invasion, and matrix remodeling. Overexpression or activation of DDR1 in various pathological scenarios makes it a potential therapeutic target for the treatment of cancer, fibrosis, atherosclerosis, and neuropsychiatric, psychiatric, and neurodegenerative disorders. In this review, we summarize current therapeutic approaches targeting DDR1 from a medicinal chemistry perspective. Furthermore, we analyze factors other than issues of low selectivity and risk of resistance, contributing to the infrequent success of DDR1 inhibitors. The complex interplay between DDR1 and the extracellular matrix (ECM) necessitates additional validation, given that DDR1 might exhibit complex and synergistic interactions with other signaling molecules during ECM regulation. The mechanisms involved in DDR1 regulation in cancer and inflammation-related diseases also remain unknown.

Multiplex immunohistochemistry elucidates increased distance between cytotoxic T cells and plasma cells in relapsed myeloma, and identifies Lag-3 as the most common checkpoint receptor on cytotoxic T cells of myeloma patients

A dysfunctional immune tumor microenvironment facilitates disease progression in multiple myeloma (MM). Using multiplex immunohistochemistry (mIHC), we describe the quantitative and qualitative changes in CD3+CD8+ cytotoxic T cells and assess their proximity to malignant plasma cells (PC) in patients with monoclonal gammopathy of undetermined significance (MGUS), and newly diagnosed (ND) and relapsed and/or refractory (RR) MM. Formalin-fixed, paraffin-embedded trephine sections from patients with MGUS (N=32), NDMM (N=65), and RRMM (N=59) were sequentially stained for CD138, CD3, CD8, and checkpoint receptors (CPR) Tim-3, Lag-3, and PD-1. The Halo® image analysis platform was used for cell segmentation and phenotyping, facilitating enumeration of cytotoxic T cells and analysis of proximity to PC. The percentage of CD8+ cytotoxic T cells in proximity to PC is greater in patients with NDMM than patients with RRMM (at 50 μm distance, 90.8% vs. 81.5%; P=0.038). There is a trend for more CD3+ T cells in MGUS (P=0.08) but no difference was observed in the prevalence of CD8+ cytotoxic T cells (P=0.48). Lag-3 is the most common CPR expressed on cytotoxic T cells in myeloma (P<0.0001), while PD-1 is the most common CPR on CD8- T cells of patients with MGUS and RRMM. Our study is the first to report on the spatial relationship between T cells and PC using mIHC on FFPE bone marrow trephine sections from patients with PC dyscrasia. The proximity of T cells to PC during early stages of MM, and overexpression of Lag-3, validate the move of immune therapeutic strategies, including T-cell engagers and checkpoint inhibitors, to upfront treatment or in early-line treatment of MM.

Prediction of immunotherapy responsiveness in melanoma through single-cell sequencing-based characterization of the tumor immune microenvironment

Immune checkpoint inhibitors (ICB) therapy have emerged as effective treatments for melanomas. However, the response of melanoma patients to ICB has been highly heterogenous. Here, by analyzing integrated scRNA-seq datasets from melanoma patients, we revealed significant differences in the TiME composition between ICB-resistant and responsive tissues, with resistant or responsive tissues characterized by an abundance of myeloid cells and CD8+ T cells or CD4+ T cell predominance, respectively. Among CD4+ T cells, CD4+ CXCL13+ Tfh-like cells were associated with an immunosuppressive phenotype linked to immune escape-related genes and negative regulation of T cell activation. We also develop an immunotherapy response prediction model based on the composition of the immune compartment. Our predictive model was validated using CIBERSORTx on bulk RNA-seq datasets from melanoma patients pre- and post-ICB treatment and showed a better performance than other existing models. Our study presents an effective immunotherapy response prediction model with potential for further translation, as well as underscores the critical role of the TiME in influencing the response of melanomas to immunotherapy.

A pH/ROS dual-responsive system for effective chemoimmunotherapy against melanoma via remodeling tumor immune microenvironment

Chemotherapeutics can induce immunogenic cell death (ICD) in tumor cells, offering new possibilities for cancer therapy. However, the efficiency of the immune response generated is insufficient due to the inhibitory nature of the tumor microenvironment (TME). Here, we developed a pH/reactive oxygen species (ROS) dual-response system to enhance chemoimmunotherapy for melanoma. The system productively accumulated in tumors by specific binding of phenylboronic acid (PBA) to sialic acids (SA). The nanoparticles (NPs) rapidly swelled and released quercetin (QUE) and doxorubicin (DOX) upon the stimulation of tumor microenvironment (TME). The in vitro and in vivo results consistently demonstrated that the NPs improved anti-tumor efficacy and prolonged survival of mice, significantly enhancing the effects of the combination. Our study revealed DOX was an ICD inducer, stimulating immune responses and promoting maturation of dendritic cells (DCs). Additionally, QUE served as a TME regulator by inhibiting the cyclooxygenase-2 (COX2)-prostaglandin E2 (PGE2) axis, which influenced various immune cells, including increasing cytotoxic T cells (CLTs) infiltration, promoting M1 macrophage polarization, and reducing regulatory T cells (Tregs) infiltration. The combination synergistically facilitated chemoimmunotherapy efficacy by remodeling the immunosuppressive microenvironment. This work presents a promising strategy to increase anti-tumor efficiency of chemotherapeutic agents.

5-Fluorouracil resistant CRC cells derived exosomes promote cancer-associated fibroblasts secreting more CXCL12

Background: Chemoresistance is a key reason for treatment failure in colorectal cancer (CRC) patients. The tumor microenvironment of chemoresistant CRC is distinctly immunosuppressive, although the underlying mechanisms are unclear. Methods: The CRC data sets GSE69657 and GSE62080 were downloaded from the GEO database, and the correlation between TRPC5 and FAP expression was analyzed by Pearson method. The in-situ expression of transient receptor potential channel 5 (TRPC5) and fibroblast activation protein (FAP) in the CRC tissues was examined by immunohistochemistry. TRPC5 expression levels in the HCT8 and HCT116 cell lines and the corresponding 5-fluorouracil (5-FU)-resistant cell lines (HCT8R and HCT116R) were analyzed by western blotting and RT-PCR. Exosomes were isolated from the HCT8R and HCT116R cells and incubated with colorectal normal fibroblasts (NFs), and cancer-associated fibroblasts (CAFs)markers were detected. NFs were also incubated with exosomes isolated from TRPC5-knockdown HCT8R cells, and the changes in intracellular Ca2+ levels and C-X-C motif chemokine ligand 12 (CXCL12) secretion were analyzed. Results: TRPC5 and FAP expression showed positive correlation in the datasets. Immunostaining of CRC tissue specimens further revealed that high TRPC5 and FAP expressions were significantly associated with worse tumor regression. Furthermore, chemoresistant CRC cells expressed higher levels of TRPC5 compared to the chemosensitive cells, and knocking down TRPC5 reversed chemoresistance. Exosomes derived from CRC cells induced the transformation of NFs to CAFs. However, TRPC5-exosomes derived from chemoresistant CRC cells can promote CAFs to secrete more CXCL12. Conclusion: Chemoresistant CRC cells can induce CAFs activation and promote CXCL12 secretion through exosomal TRPC5.