Unlocking the crucial role of cancer-associated fibroblasts in tumor metastasis: Mechanisms and therapeutic prospects.

BACKGROUND: Tumor metastasis represents a stepwise progression and stands as a principal determinant of unfavorable prognoses among cancer patients. Consequently, an in-depth exploration of its mechanisms holds paramount clinical significance. Cancer-associated fibroblasts (CAFs), constituting the most abundant stromal cell population within the tumor microenvironment (TME), have garnered robust evidence support for their pivotal regulatory roles in tumor metastasis. AIM OF REVIEW: This review systematically explores the roles of CAFs at eight critical stages of tumorigenic dissemination: 1) extracellular matrix (ECM) remodeling, 2) epithelial-mesenchymal transition (EMT), 3) angiogenesis, 4) tumor metabolism, 5) perivascular migration, 6) immune escape, 7) dormancy, and 8) premetastatic niche (PMN) formation. Additionally, we provide a compendium of extant strategies aimed at targeting CAFs in cancer therapy. KEY SCIENTIFIC CONCEPTS OF REVIEW: This review delineates a structured framework for the interplay between CAFs and tumor metastasis while furnishing insights for the potential therapeutic developments. It contributes to a deeper understanding of cancer metastasis within the TME, facilitating the utilization of CAF-targeting therapies in anti-metastatic approaches.

Clinicopathological significance and prognostic analysis of p21 and EGFR in colorectal cancer: a retrospective analysis on 12 319 cases in China.

AIMS: Colorectal cancer (CRC) is the third most common malignancy worldwide. Accurate pathological diagnosis and predictive abilities for treatment response and prognosis are crucial for patients with CRC. This study aims to analyse the expressions of p21 and EGFR in CRC and their relationships with clinicopathological characteristics and prognosis to enhance diagnostic and prognostic evaluations. METHODS: This study conducted a retrospective analysis of p21 and EGFR expressions in 12 319 Chinese patients with CRC using immunohistochemistry. The relationships between these expressions and clinicopathological characteristics and survival outcomes were explored through statistical and survival analyses. RESULTS: Differential expressions of p21 and EGFR in CRC were closely related to clinicopathological characteristics and significantly impacted overall survival (OS). p21 expression was associated with the primary tumour site, mucinous subtype, lymphovascular invasion, perineural invasion, circumferential resection margin, T stage, N stage, tumour, node, metastases (TNM) stage, and mismatch repair status. EGFR expression was related to mucinous subtype, tumour differentiation, lymphovascular invasion, perineural invasion, tumour size, T stage, N stage, TNM stage and BRAF gene mutation. p21 and EGFR expressions were positively correlated (r=0.11). High p21 expression correlated with favourable OS, whereas high EGFR expression predicted poorer OS. A prognostic nomogram incorporating these biomarkers and clinical variables demonstrated robust predictive power for patient survival rates. CONCLUSION: p21 and EGFR serve as potential indicators for pathological diagnosis, risk stratification, and predicting treatment efficacy and prognosis in patients with CRC. The study's findings provide valuable references for personalised treatment and prognosis evaluation in clinical practice.

Finding the minimum number of retrieved lymph nodes and negative lymph nodes in gastric cancer surgery: a real-world study.

BACKGROUND: Lymph node retrieval deficiency can lead to understagement and postoperative cancer recurrence, it is crucial to establish the standard number of retrieved lymph nodes (rLNs) and negative lymph nodes (nLNs) for patients undergoing gastrectomy. METHODS: Patients who has gastric adenocarcinoma and underwent either radical subtotal gastrectomy (RSG) or radical total gastrectomy (RTG) between 2000 and 2022 were retrospectively included. We utilized restricted cubic spline (RCS) analysis to determine the ideal threshold for rLNs and nLNs. Survival analysis was conducted using Kaplan-Meier (KM) curves, log-rank tests and forest plots. Propensity score matching (PSM) was utilized to balance parameters between two groups. The median follow-up time for this study was 3,095 days. RESULTS: Our study found that there are significant tumor characteristic differences between RSG and RTG. For patients with N0-N3a stage undergoing RSG, retrieving≥24 lymph nodes intraoperatively were associated with better prognosis both before and after PSM (OS: P<0.001, P=0.019); whereas for N3b stage, at least 32 rLNs were required (OS: P=0.006, P=0.023). Similarly, for patients with N0-N3a stage undergoing RTG, retrieving≥27 lymph nodes intraoperatively were associated with better prognosis both before and after PSM (OS: P<0.001, P=0.047); whereas for N3b stage, at least 34 rLNs were required (OS: P<0.001, P=0.003). Additionally, for patients undergoing RSG, having ≥21 nLNs (OS: P<0.001, P=0.013), and for those undergoing RTG, having ≥22 nLNs (OS: P<0.001, P<0.001), were also associated with better prognosis both before and after PSM. CONCLUSIONS: For patients receiving RSG, rLNs should reach 24 when lymph nodes are limited, and 32 when lymph node metastasis is more extensive, with a minimum number of nLNs ideally reaching 21. Similarly, for patients receiving RTG, rLNs should reach 27 when lymph nodes are limited, 34 when lymph node metastasis is more extensive, and a minimum number of nLNs ideally reaching 22.

Prostate cancer-associated transcript 6 (PCAT6) promotes epithelial-mesenchymal transition and stemness and worsens prognosis in patients with colorectal cancer.

Approximately 20% of colorectal cancer (CRC) patients are first diagnosed with metastatic colorectal cancer (mCRC) because they develop symptoms at an advanced stage. Despite advancements in treatment, patients with metastatic disease still experience inferior survival rates. Our objective is to investigate the association between long noncoding RNAs (lncRNAs) and prognosis and to explore their role in mCRC. In this study, we find that elevated expression of PCAT6 is independently linked to unfavourable survival outcomes in The Cancer Genome Atlas (TCGA) data, and this finding is further confirmed in CRC samples obtained from Fudan University Shanghai Cancer Center. Cell lines and xenograft mouse models are used to examine the impact of PCAT6 on tumor metastasis. Knockdown of PCAT6 is observed to impede the metastatic phenotype of CRC, as evidenced by functional assays, demonstrating the suppression of epithelial-mesenchymal transition (EMT) and stemness. Our findings show the significance of PCAT6 in mCRC and its potential use as a prognostic biomarker.

Integration Analysis of Single-Cell Multi-Omics Reveals Prostate Cancer Heterogeneity.

Prostate cancer (PCa) is an extensive heterogeneous disease with a complex cellular ecosystem in the tumor microenvironment (TME). However, the manner in which heterogeneity is shaped by tumors and stromal cells, or vice versa, remains poorly understood. In this study, single-cell RNA sequencing, spatial transcriptomics, and bulk ATAC-sequence are integrated from a series of patients with PCa and healthy controls. A stemness subset of club cells marked with SOX9highARlow expression is identified, which is markedly enriched after neoadjuvant androgen-deprivation therapy (ADT). Furthermore, a subset of CD8+CXCR6+ T cells that function as effector T cells is markedly reduced in patients with malignant PCa. For spatial transcriptome analysis, machine learning and computational intelligence are comprehensively utilized to identify the cellular diversity of prostate cancer cells and cell-cell communication in situ. Macrophage and neutrophil state transitions along the trajectory of cancer progression are also examined. Finally, the immunosuppressive microenvironment in advanced PCa is found to be associated with the infiltration of regulatory T cells (Tregs), potentially induced by an FAP+ fibroblast subset. In summary, the cellular heterogeneity is delineated in the stage-specific PCa microenvironment at single-cell resolution, uncovering their reciprocal crosstalk with disease progression, which can be helpful in promoting PCa diagnosis and therapy.

The role of transcription factors in the crosstalk between cancer-associated fibroblasts and tumor cells.

BACKGROUND: Transcription factors (TFs) fulfill a critical role in the formation and maintenance of different cell types during the developmental process as well as disease. It is believed that cancer-associated fibroblasts (CAFs) are activation status of tissue-resident fibroblasts or derived from form other cell types via transdifferentiation or dedifferentiation. Despite a subgroup of CAFs exhibit anti-cancer effects, most of them are reported to exert effects on tumor progression, further indicating their heterogeneous origin. AIM OF REVIEW: This review aimed to summarize and review the roles of TFs in the reciprocal crosstalk between CAFs and tumor cells, discuss the emerging mechanisms, and their roles in cell-fate decision, cellular reprogramming and advancing our understanding of the gene regulatory networks over the period of cancer initiation and progression. KEY SCIENTIFIC CONCEPTS OF REVIEW: This manuscript delves into the key contributory factors of TFs that are involved in activating CAFs and maintaining their unique states. Additionally, it explores how TFs play a pivotal and multifaceted role in the reciprocal crosstalk between CAFs and tumor cells. This includes their involvement in processes such as epithelial-mesenchymal transition (EMT), proliferation, invasion, and metastasis, as well as metabolic reprogramming. TFs also have a role in constructing an immunosuppressive microenvironment, inducing resistance to radiation and chemotherapy, facilitating angiogenesis, and even 'educating' CAFs to support the malignancies of tumor cells. Furthermore, this manuscript delves into the current status of TF-targeted therapy and considers the future directions of TFs in conjunction with anti-CAFs therapies to address the challenges in clinical cancer treatment.

Structure-aware deep model for MHC-II peptide binding affinity prediction.

The prediction of major histocompatibility complex (MHC)-peptide binding affinity is an important branch in immune bioinformatics, especially helpful in accelerating the design of disease vaccines and immunity therapy. Although deep learning-based solutions have yielded promising results on MHC-II molecules in recent years, these methods ignored structure knowledge from each peptide when employing the deep neural network models. Each peptide sequence has its specific combination order, so it is worth considering adding the structural information of the peptide sequence to the deep model training. In this work, we use positional encoding to represent the structural information of peptide sequences and validly combine the positional encoding with existing models by different strategies. Experiments on three datasets show that the introduction of position-coding information can further improve the performance built upon the existing model. The idea of introducing positional encoding to this field can provide important reference significance for the optimization of the deep network structure in the future.

Long-read transcriptome landscapes of primary and metastatic liver cancers at transcript resolution.

BACKGROUND: The liver ranks as the sixth most prevalent site of primary cancer in humans, and it frequently experiences metastases from cancers originating in other organs. To facilitate the development of effective treatments and improve survival rates, it is crucial to comprehend the intricate and diverse transcriptome landscape of primary and metastatic liver cancers. METHODS: We conducted long-read isoform sequencing and short-read RNA sequencing using a cohort of 95 patients with primary and secondary liver cancer who underwent hepatic resection. We compared the transcriptome landscapes of primary and metastatic liver cancers and systematically investigated hepatocellular carcinoma (HCC), paired primary tumours and liver metastases, and matched nontumour liver tissues. RESULTS: We elucidated the full-length isoform-level transcriptome of primary and metastatic liver cancers in humans. Our analysis revealed isoform-level diversity in HCC and identified transcriptome variations associated with liver metastatis. Specific RNA transcripts and isoform switching events with clinical implications were profound in liver cancer. Moreover, we defined metastasis-specific transcripts that may serve as predictors of risk of metastasis. Additionally, we observed abnormalities in adjacent paracancerous liver tissues and characterized the immunological and metabolic alterations occurring in the liver. CONCLUSIONS: Our findings underscore the power of full-length transcriptome profiling in providing novel biological insights into the molecular mechanisms underlying tumourigenesis. These insights will further contribute to improving treatment strategies for primary and metastatic liver cancers.

Homology Identification and Cross-Contamination Analysis: A Method for Evaluating the Quality of Biological Samples Stored in a Biobank Using the Advanta Sample ID Genotyping Panel.

Biological samples are important resources for scientific research. These samples are stored in biobanks over years until needed, and some of them can never be retrieved if they are improperly stored, causing them to be wasted. Thus, they are priceless, and they should be used correctly and effectively. Sample quality substantially affects biomedical research results. However, sample misidentification or mix-up is common. It is necessary to establish quality standards for sample identification. In this study, we used the Advanta Sample ID genotyping panel to detect homology identification and cross-contamination. We compared the single-nucleotide polymorphism (SNP) typing results of two different samples and calculated the similarity score of homologous sample pairs and nonhomologous sample pairs. Through analysis, we obtained a similarity score cutoff point of 0.8620, which was an effective way to distinguish homology and nonhomology. Cross-contamination was detected in two sets of mixtures (STD8:STD6 and jj3:1-P) mixed at a series of special ratios. Sensitivity was dependent on the sample characteristics and mixing ratios. Finally, we assessed the effect of sample degradation degree on SNP genotyping and found that degraded samples with a minimal DNA integrity number of 1.9 had complete genotyping results. On the whole, this study shows that the Sample ID panel is reliable for homology identification and cross-contamination analysis. Moreover, this technology has promising further applications in biological sample quality control.

Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network.

BACKGROUND: Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC. METHODS: We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth. RESULTS: NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%). CONCLUSIONS: By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace.

Gambogenic acid inhibits proliferation and ferroptosis by targeting the miR-1291/FOXA2 and AMPKα/SLC7A11/GPX4 axis in colorectal cancer.

The present study aims to investigate the mechanism of the nature compound gambogenic acid (GNA) on the apoptosis and ferroptosis in colorectal cancer (CRC). The effect of GNA on the proliferation of CRC cell lines were detected by MTT and clonogenic assay. The xenograft tumor model was established, and the inhibition effect of GNA were evaluated by observing the tumor growth. The endoplasmic reticulum (ER) of HCT116 was observed by using the ER tracker. The TargrtScan database was used to predict the miRNA binding sites. The level of miRNA with GNA treatment was explored by real-time quantitative PCR. The effect of ferroptosis were evaluated by detect the expression of reactive oxygen species (ROS), intracellular ferrous iron (Fe2+ ), malondialdehyde (MDA), glutathione (GSH), subunit solute carrier family 7 member 11 (SLC7A11), glutathione peroxidase (GPX)4, transferrin, and ferritin by Western blot. GNA isolated from gamboge can inhibit the growth and proliferation of CRC cell lines in a concentration-dependent manner. GNA activated ER stress by upregulating miR-1291, and miR-1291 targeted the forkhead box protein A2 (FOXA2). GNA also induced ROS production and mediated the Fenton reaction by activating transferrin to increase Fe2+ , thus inducing ferroptosis. In addition, GNA could induce ferroptosis through the depletion of GSH and GPX4. Furthermore, GNA treatment regulated iron metabolism by activating AMPKα/SLC7A11/GPX4 signaling. In conclusion, GNA activated ER stress via miR-1291 and induced ferroptosis in CRC cells and might be a new inducer of ferroptosis, which can expand the efficacy of chemotherapy drugs.

Enhanced BCAT1 activity and BCAA metabolism promotes RhoC activity in cancer progression.

Increased expression of branched-chain amino acid transaminase 1 or 2 (BCAT1 and BCAT2) has been associated with aggressive phenotypes of different cancers. Here we identify a gain of function of BCAT1 glutamic acid to alanine mutation at codon 61 (BCAT1E61A) enriched around 2.8% in clinical gastric cancer samples. We found that BCAT1E61A confers higher enzymatic activity to boost branched-chain amino acid (BCAA) catabolism, accelerate cell growth and motility and contribute to tumor development. BCAT1 directly interacts with RhoC, leading to elevation of RhoC activity. Notably, the BCAA-derived metabolite, branched-chain α-keto acid directly binds to the small GTPase protein RhoC and promotes its activity. BCAT1 knockout-suppressed cell motility could be rescued by expressing BCAT1E61A or adding branched-chain α-keto acid. We also identified that candesartan acts as an inhibitor of BCAT1E61A, thus repressing RhoC activity and cancer cell motility in vitro and preventing peritoneal metastasis in vivo. Our study reveals a link between BCAA metabolism and cell motility and proliferation through regulating RhoC activation, with potential therapeutic implications for cancers.

PROX1-mediated epigenetic silencing of SIRT3 contributes to proliferation and glucose metabolism in colorectal cancer.

Prospero-related homeobox 1 (PROX1) is a homeobox transcription factor known to promote malignant transformation and stemness in human colorectal cancer (CRC). However, the biological function of PROX1 in metabolic rearrangement in CRC remains unclear. Here, we aimed to uncover the relationship between the expression profile and role of PROX1 and CRC cell glucose metabolism and to elucidate the underlying molecular mechanism. PROX1 expression was significantly upregulated in human CRC tissues and positively associated with the maximum standardized uptake value (SUVmax), a measure of tissue 18-fluoro-2-deoxy-D-glucose uptake and an indicator of glycolysis and tumor cell activity, in patients with CRC. Knockdown of PROX1 suppressed CRC cell proliferation and glucose metabolism in vitro and in vivo. Mechanistically, through a physical interaction, PROX1 recruited EZH2 to the SIRT3 promoter and inhibited SIRT3 promoter activity. Moreover, PROX1 or EZH2 knockdown decreased cell glycolysis by targeting SIRT3. Clinically, high PROX1 expression combined with low SIRT3 expression predicted poor prognosis in patients with CRC. Thus, our study suggests that the PROX1-EZH2 complex positively regulates cell proliferation and glucose metabolism by engaging SIRT3 in CRC, which may serve as a promising therapeutic strategy for CRC.

Comprehensive analysis of immune subtypes reveals the prognostic value of cytotoxicity and FAP+ fibroblasts in stomach adenocarcinoma.

BACKGROUND: The heterogeneity limits the effective application of immune checkpoint inhibitors for patients with stomach adenocarcinoma (STAD). Precise immunotyping can help select people who may benefit from immunotherapy and guide postoperative management by describing the characteristics of tumor microenvironment. METHODS: Gene expression profiles and clinical information of patients were collected from ACRG and TCGA-STAD datasets. The immune subtypes (ISs) were identified by consensus clustering analysis. The tumor immune microenvironments (TIME) of each IS were characterized using a series of immunogenomics methods and further confirmed by multiplex immunohistochemistry (mIHC) staining in clinical samples. Two online datasets and one in-house dataset were utilized to construct and validate a prognostic immune-related gene (IRG) signature. RESULTS: STAD patients were stratified into five reproducible ISs. IS1 (immune deserve subtype) had low immune infiltration and the highest degree of HER2 gene mutation. With abundant CD8+ T cells infiltration and activated cytotoxicity reaction, patients in the IS2 (immune-activated subtype) had the best overall survival (OS). IS3 and IS4 subtypes were both in the reactive stroma state and indicated the worst prognosis. However, IS3 (immune-inhibited subtype) was characterized by enrichment of FAP+ fibroblasts and upregulated TGF-ß signaling pathway, while IS4 (activated stroma subtype) was characterized by enrichment of ACTA2+ fibroblasts. In addition, mIHC staining confirmed that TGF-ß upregulated FAP+ fibroblasts were independent risk factor of OS. IS5 (chronic inflammation subtype) displayed moderate immune cells infiltration and had a relatively good survival. Lastly, we developed a nine-IRG signature model with a robust performance on overall survival prognostication. CONCLUSIONS: The immunotyping is indicative for characterize the TIME heterogeneity and the prediction of tumor prognosis for STADs, which may provide valuable stratification for the design of future immunotherapy.

Calcipotriol abrogates cancer-associated fibroblast-derived IL-8-mediated oxaliplatin resistance in gastric cancer cells via blocking PI3K/Akt signaling.

Activation of vitamin D receptor (VDR) in cancer-associated fibroblasts (CAFs) has been implicated in hesitating tumor progression and chemoresistance of several human malignancies. Yet, the role of VDR in CAF-induced chemotherapy resistance of gastric cancer (GC) cells remains elusive. In this study we first conducted immunohistochemistry analysis on tissue microarrays including 88 pairs of GC and normal mucosa samples, and provided clinical evidence that VDR was mainly expressed in gastric mucous cells but almost invisible in CAFs, and VDR expression was negatively correlated with malignant clinical phenotype and advanced stages, low VDR expression confers to poor overall survival rate of patients with GC. In a co-culture system of primary CAFs and cancer cells, we showed that treatment of HGC-27 and AGS GC cells with VDR ligand calcipotriol (Cal, 500 nM) significantly inhibited CAF-induced oxaliplatin resistance. By using RNA-sequencing and Human Cytokine Antibody Array, we demonstrated that IL-8 secretion from CAFs induced oxaliplatin resistance via activating the PI3K/AKT pathway in GC, whereas Cal treatment greatly attenuated the tumor-supportive effect of CAF-derived IL-8 on GC cells. Taken together, this study verifies the specific localization of VDR in GC tissues and demonstrates that activation of VDR abrogates CAF-derived IL-8-mediated oxaliplatin resistance in GC via blocking PI3K/Akt signaling, suggesting vitamin D supplementation as a potential strategy of enhancing the anti-tumor effect of chemotherapy in GC.

Transcriptomic characterization and construction of M2 macrophage-related prognostic and immunotherapeutic signature in ovarian metastasis of gastric cancer.

BACKGROUND: Ovarian metastasis (OM) poses a major threat to the outcome of gastric cancer (GC) patients. Recently, immunotherapy emerged as a novel promising therapeutic strategy to treat late-stage GC, whereas its efficacy is influenced by tumor immune microenvironment (TIME). M2 macrophage, a key subset within TIME, plays dual immunosuppressive and pro-tumorigenic roles in cancer progression and is recognized as a potential therapeutic target. However, molecular mechanisms underlying OM remain elusive and the TIME-related prognostic and immunotherapeutic index for these patients is yet to establish. METHODS: Differential expressed genes (DEGs) between paired normal mucosa, primary GC and OM of patients from Fudan University Shanghai Cancer Center (FUSCC) cohort (n = 6) were identified by transcriptome sequencing, followed by the functional annotation of enriched hallmark pathways of DEGs between them. CIBERSORT was used to profile the relative expression level of 22 immune cell subsets in normal tissues, primary and metastatic tumors, followed by weighted gene coexpression network analysis (WGCNA) uncovering immune cell-correlated gene sets. The intersected genes between DEGs and M2 macrophage-related genes were processed by least absolute shrinkage and selection operator (LASSO) regression analysis to construct a predictive signature, M2GO, which was further validated by training set and test set of The Cancer Genome Atlas-Stomach Adenocarcinoma (TCGA-STAD), GSE62254 and GSE84437 cohorts. GC patients were divided into M2GO-high and -low subgroup according to the optimal cutoff value of the M2GO score. Furthermore, the clinical, molecular and immune features between M2GO-high and -low subgroups were analyzed. Clinical cohorts of immunotherapy were used to validate the predictive value of M2GO in regard to immunotherapy effectiveness. RESULTS: Transcriptomic sequencing and follow-up analyses of triple-matched normal tissues, primary and ovarian metastatic tumors identified distinctive sets of DEGs and enriched immune-, cancer- and metastasis-related pathways between them. Of note, M2 macrophage, a major immunosuppressive and pro-tumorigenic component within TIME, was significantly up-regulated in OMs. WGCNA and LASSO regression were applied to establish a novel OM- and M2 macrophage-related predictive signature, M2GO, based on M2 macrophage-related prognostic genes including GJA1, MAGED1 and SERPINE1. M2GO served as an independent prognostic factor of GC patients. Comprehensive molecular and immune characterization of M2GO-based subgroups uncovered their distinctive features in terms of enriched functional pathways, tumor mutation burden, key immune checkpoints, major regulators of natural immune cGAS-STING pathway, infiltrated subsets of immune cells and tumor immune exclusion/dysfunction (TIDE) score. Notably, the M2GO score was significantly lower in responsive group than non-responsive group (P < 0.05) in clinical cohort of metastatic GC patients undergoing immunotherapy. CONCLUSION: Transcriptomic characterization of paired normal mucosae, primary and ovarian metastatic tumors revealed their unique molecular and immune features. Follow-up analyses established a novel OM- and M2 macrophage-related signature, M2GO, which served as a promising prognostic and immunotherapeutic biomarker to distinguish the clinical outcome, molecular and immune features of GC patients and predict their differential responses to immunotherapy.

Multiplexed immunofluorescence analysis of CAF-markers, EZH2 and FOXM1 in gastric tissue: associations with clinicopathological parameters and clinical outcomes.

BACKGROUND: The aim of this study is to explore the expression and clinical relevance of CAF-associated markers, EZH2 and FOXM1 in gastric samples. METHODS: Protein expression were detected and evaluated by multi-plex immunofluorescence (mIF) in 93 cases of gastric cancer (GC) and 31 cases of gastric intraepithelial neoplasia (GIN). The correlation among their expression, and the relationship of them with clinicopathological parameters and prognosis in GC were then analyzed. RESULTS: FAP was specific expressed in the CAFs of GC samples, and thus be utilized as a CAF-associated marker in our subsequently analysis. The immunostaining of EZH2, FOXM1 and FAP were significantly upregulated in patients with GC tissues than in those normal gastric mucosa or GIN tissues. The average fluorescence intensity of FAP was slightly positively correlated with EZH2 in GC, GIN and normal samples, whereas the percentage of FAP positive cells has no correlation with that of EZH2. Both the percentage of positive cells and the average fluorescence intensity of FOXM1 were positively correlated with that of FAP and EZH2 in GC, GIN and normal samples, except for FOXM1 and EZH2 expression in normal tissue samples. No significant association was observed between FAP expression and any clinicopathological parameters, whereas the positive frequency of EZH2 and FOXM1 were correlated with tumor location significantly and tumor invasion depth, respectively. In addition, there was strong positive correlations between FAP protein expression and overall survival (OS) and disease-free survival (DFS), and EZH2 expression was positively associated with OS in patients with GC. Furthermore, EZH2 and FAP protein expression was an independent prognostic factor for OS and DFS, respectively. CONCLUSIONS: These results suggest that both EZH2 and FOXM1 expression was positively associated with CAFs abundance in GC. They may be potential cellular target for therapeutic intervention, especially in patients with a large number of CAFs.

The role of cancer-associated fibroblasts in tumorigenesis of gastric cancer.

Despite advances in anticancer therapy, the prognosis of gastric cancer (GC) remains unsatisfactory. Research in recent years has shown that the malignant behavior of cancer is not only attributable to tumor cells but is partly mediated by the activity of the cancer stroma and controlled by various molecular networks in the tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs) are one of the most abundant mesenchymal cell components of the stroma and extensively participate in the malignant development of GC malignancy. CAFs modulate the biological properties of tumor cells in multiple ways, including the secretion of various bioactive molecules that have effects through paracrine and autocrine signaling, the release of exosomes, and direct interactions, thereby affecting GC initiation and development. However, there is marked heterogeneity in the cellular origins, phenotypes, and functions of CAFs in the TME of GC. Furthermore, variations in factors, such as proteins, microRNAs, and lncRNAs, affect interactions between CAFs and GC cells, although, the potential molecular mechanisms are still poorly understood. In this review, we aim to describe the current knowledge of the cellular features and heterogeneity of CAFs and discuss how these factors are regulated in CAFs, with a focus on how they affect GC biology. This review provides mechanistic insight that could inform therapeutic strategies and improve the prognosis of GC patients.

The immune subtypes and landscape of sarcomas.

BACKGROUND: Considering the molecular heterogeneity of sarcomas and their immunologically quiet character, immunotherapy (e.g., immune checkpoint inhibitors) plays a viable role in only a subset of these tumors. This study aimed to determine the immune subtypes (IMSs) of sarcomas for selecting suitable patients from an extremely heterogeneous population. RESULTS: By performing consensus clustering analysis of the gene expression profiles of 538 patients with sarcomas in online databases, we stratified sarcomas into three IMSs characterized by different immune cell features, tumor mutational burdens (TMBs), gene mutations, and clinical outcomes. IMS1 showed an immune "hot" and immunosuppressive phenotype, the highest frequencies of CSMD3 mutation but the lowest frequencies of HMCN1 and LAMA2 mutations; these patients had the worst progression-free survival (PFS). IMS2 was defined by a high TMB and more gene mutations, but had the lowest frequency of MND1 mutations. IMS3 displayed the highest MDN1 expression level and an immune "cold" phenotype, these patients had the worst PFS. Each subtype was associated with different expression levels of immunogenic cell death modulators and immune checkpoints. Moreover, we applied graph learning-based dimensionality reduction to the immune landscape and identified significant intra-cluster heterogeneity within each IMS. Finally, we developed and validated an immune gene signature with good prognostic performance. CONCLUSIONS: Our results provide a conceptual framework for understanding the immunological heterogeneity of sarcomas. The identification of immune-related subtypes may facilitate optimal selection of sarcoma patients who will respond to appropriate therapeutic strategies.

Evolutionary Trajectories of Primary and Metastatic Pancreatic Neuroendocrine Tumors Based on Genomic Variations.

Liver metastases are common in pancreatic neuroendocrine tumors (PanNETs) patients and they are considered a poor prognostic marker. This study aims to analyze the spatiotemporal patterns of genomic variations between primary and metastatic tumors, and to identify the key related biomolecular pathways. We performed next-generation sequencing on paired tissue specimens of primary PanNETs (n = 11) and liver metastases (n = 12). Low genomic heterogeneity between primary PanNETs and liver metastases was observed. Genomic analysis provided evidence that polyclonal seeding is a prevalent event during metastatic progression, and may be associated with the progression-free survival. Besides this, copy number variations of BRCA1/BRCA2 seem to be associated with better prognosis. Pathways analysis showed that pathways in cancer, DNA repair, and cell cycle regulation-related pathways were significantly enriched in primary PanNETs and liver metastases. The study has shown a high concordance of gene mutations between the primary tumor and its metastases and the shared gene mutations may occur during oncogenesis and predates liver metastasis, suggesting an earlier onset of metastasis in patients with PanNETs, providing novel insight into genetic changes in metastatic tumors of PanNETs.