Identification of an Immune Signature Predicting Prognosis Risk and Lymphocyte Infiltration in Colon Cancer

Impacts of Nutlin-3a and exercise on murine double minute 2-enriched glioma treatment

JOURNAL/nrgr/04.03/01300535-202504000-00029/figure1/v/2024-07-06T104127Z/r/image-tiff Recent research has demonstrated the impact of physical activity on the prognosis of glioma patients, with evidence suggesting exercise may reduce mortality risks and aid neural regeneration. The role of the small ubiquitin-like modifier (SUMO) protein, especially post-exercise, in cancer progression, is gaining attention, as are the potential anti-cancer effects of SUMOylation. We used machine learning to create the exercise and SUMO-related gene signature (ESLRS). This signature shows how physical activity might help improve the outlook for low-grade glioma and other cancers. We demonstrated the prognostic and immunotherapeutic significance of ESLRS markers, specifically highlighting how murine double minute 2 (MDM2), a component of the ESLRS, can be targeted by nutlin-3. This underscores the intricate relationship between natural compounds such as nutlin-3 and immune regulation. Using comprehensive CRISPR screening, we validated the effects of specific ESLRS genes on low-grade glioma progression. We also revealed insights into the effectiveness of Nutlin-3a as a potent MDM2 inhibitor through molecular docking and dynamic simulation. Nutlin-3a inhibited glioma cell proliferation and activated the p53 pathway. Its efficacy decreased with MDM2 overexpression, and this was reversed by Nutlin-3a or exercise. Experiments using a low-grade glioma mouse model highlighted the effect of physical activity on oxidative stress and molecular pathway regulation. Notably, both physical exercise and Nutlin-3a administration improved physical function in mice bearing tumors derived from MDM2-overexpressing cells. These results suggest the potential for Nutlin-3a, an MDM2 inhibitor, with physical exercise as a therapeutic approach for glioma management. Our research also supports the use of natural products for therapy and sheds light on the interaction of exercise, natural products, and immune regulation in cancer treatment.

Arctigenin inhibits the progression of colorectal cancer through epithelial-mesenchymal transition via PI3K/Akt/mTOR signaling pathway

BACKGROUND

Colorectal cancer (CRC) is a significant disease worldwide, with high mortality rates. Conventional treatment methods often lead to metastasis and drug resistance, highlighting the need to explore new drugs and their potential molecular mechanisms. In this study, we investigated the effects of arctigenin on CRC cell proliferation, migration, invasion, apoptosis, and related protein expression, as well as its potential molecular mechanisms.

METHODS

The CCK-8 assay, transwell migration and invasion assays, flow cytometry, immunoblotting and immunofluorescence staining, western blot and an allograft tumor transplantation model was used.

RESULTS

Our study revealed that arctigenin effectively inhibited CRC cell proliferation, migration, and invasion in a dose-dependent manner, while also inducing apoptosis. At the molecular level, arctigenin significantly downregulated the expressions of PCNA, Bcl2, MMP-2, and MMP-9 and upregulated the expressions of Bax and cleaved caspase-3. Additionally, arctigenin demonstrated the ability to inhibit the epithelial-mesenchymal transition (EMT) process by upregulating E-cadherin and downregulating mesenchymal markers, such as N-cadherin, Vimentin, Snail, and Slug. Furthermore, arctigenin could inhibit the activation of the PI3K-AKT-mTOR signaling pathway, which has been implicated in cancer progression. In vivo experiments also showed that arctigenin significantly reduced tumor volume and size compared to the control group, with no significant adverse effects on the liver.

CONCLUSIONS

This is the first study to elucidate the mechanism by which arctigenin inhibits colorectal cancer metastasis through the PI3K-AKT-mTOR signaling pathway by suppressing the EMT process at the molecular level.

Myeloid‑derived suppressor cells: Key immunosuppressive regulators and therapeutic targets in colorectal cancer (Review)

Globally, colorectal cancer (CRC) is the third most common type of cancer. CRC has no apparent symptoms in the early stages of disease, and most patients receive a confirmed diagnosis in the middle or late disease stages. The incidence of CRC continues to increase, and the affected population tends to be younger. Therefore, determining how to achieve an early CRC diagnosis and treatment has become a top priority for prolonging patient survival. Myeloid‑derived suppressor cells (MDSCs) are a group of bone marrow‑derived immuno‑negative regulatory cells that are divided into two subpopulations, polymorphonuclear‑MDSCs and monocytic‑MDSCs, based on their phenotypic similarities to neutrophils and monocytes, respectively. These cells can inhibit the immune response and promote cancer cell metastasis in the tumour microenvironment (TME). A large aggregation of MDSCs in the TME is often a marker of cancer and a poor prognosis in inflammatory diseases of the intestine (such as colonic adenoma and ulcerative colitis). In the present review, the phenotypic classification of MDSCs in the CRC microenvironment are first discussed. Then, the amplification, role and metastatic mechanism of MDSCs in the CRC TME are described, focusing on genes, gene modifications, proteins and the intestinal microenvironment. Finally, the progress in CRC‑targeted therapies that aim to modulate the quantity, function and structure of MDSCs are summarized in the hope of identifying potential screening markers for CRC and improving CRC prognosis and therapeutic options.

Integrated single-cell and bulk RNA-seq analysis identifies a prognostic T-cell signature in colorectal cancer

Colorectal cancer (CRC) is a major contributor to global morbidity and mortality, necessitating more effective therapeutic approaches. T cells, prominent in the tumor microenvironment, exert a crucial role in modulating immunotherapeutic responses and clinical outcomes in CRC. This study introduces a pioneering method for characterizing the CRC immune microenvironment using single-cell sequencing data. Unlike previous approaches, which focused on individual T-cell signature genes, we utilized overall infiltration levels of colorectal cancer signature T-cells. Through weighted gene co-expression network analysis, Lasso regression, and StepCox analysis, we developed a prognostic risk model, TRGS (T-cell related genes signatures), based on six T cell-related genes. Multivariate Cox analysis identified TRGS as an independent prognostic factor for CRC, showcasing its superior predictive efficacy compared to existing immune-related prognostic models. Immunoreactivity analysis revealed higher Immunophenoscore and lower Tumor Immune Dysfunction and Exclusion scores in the low-risk group, indicating potential responsiveness to immune checkpoint inhibitor therapy. Additionally, patients in the low-risk group demonstrated heightened sensitivity to 5-fluorouracil-based chemotherapy regimens. In summary, TRGS emerges as a standalone prognostic biomarker for CRC, offering insights to optimize patient responses to immunotherapy and chemotherapy, thereby laying the groundwork for personalized tumor management strategies.

Canopy FGF signaling regulator 3 affects prognosis, immune infiltration, and PI3K/AKT pathway in colon adenocarcinoma

BACKGROUND

Colon adenocarcinoma (COAD) is a malignant tumor of the digestive system. The mechanisms underlying COAD development and progression are still largely unknown.

AIM

To identify the role of canopy FGF signaling regulator 3 (CNPY3) in the development and progression of COAD by using bioinformatic tools and functional experiments.

METHODS

Bioinformatic data were downloaded from public databases. The associations of clinicopathological features, survival, and immune function with the expression of CNPY3 were analyzed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses and Gene Set Enrichment Analysis were used to explore the related pathways. Then, quantitative real-time PCR and immunohistochemistry were used for validation of CNPY3 expression in clinical samples and tumor cell lines. Cell lines with CNPY3 knockdown were constructed to further analyze gene functions. The functional experiments included proliferation, invasion, migration and apoptosis assays.

RESULTS

In both the TCGA cohort and the merged dataset, elevated CNPY3 expression was observed in tumor tissues. High CNPY3 expression correlated with adverse survival and compromised immune functions. Functional enrichment analysis suggested that the pro-oncogenic properties of CNPY3 might be linked to the PI3K-AKT signaling pathway. CNPY3 expression was validated at both the RNA and protein levels. Functional assays indicated that cell proliferation, invasion, and migration were inhibited and cell apoptosis was promoted after CNPY3 knockdown. Additionally, Western blot results revealed the downregulation of key proteins in the PI3K/AKT pathway following CNPY3 knockdown. PI3K/AKT pathway activator reversed the decrease in proliferation, invasion, and migration and the increase in apoptosis. Notably, CNPY3 knockdown still affected the cells when the pathway was inhibited.

CONCLUSION

This study showed that CNPY3 is upregulated in COAD and might regulate COAD development and progression by the PI3K/AKT pathway. Thus, CNPY3 might be a promising therapeutic target.

Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence: A population-based study

BACKGROUND

Research on gastrointestinal mucosal adenocarcinoma (GMA) is limited and controversial, and there is no reference tool for predicting postoperative survival.

AIM

To investigate the prognosis of GMA and develop predictive model.

METHODS

From the Surveillance, Epidemiology, and End Results database, we collected clinical information on patients with GMA. After random sampling, the patients were divided into the discovery (70% of the total, for model training), validation (20%, for model evaluation), and completely blind test cohorts (10%, for further model evaluation). The main assessment metric was the area under the receiver operating characteristic curve (AUC). All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA's prognosis.

RESULTS

This model had an AUC of 0.7433 [95% confidence intervals (95%CI): 0.7424-0.7442] in the discovery cohort, 0.7244 (GMA: 0.7234-0.7254) in the validation cohort, and 0.7388 (95%CI: 0.7378-0.7398) in the test cohort. We packaged it into Windows software for doctors' use and uploaded it. Mucinous gastric adenocarcinoma had the worst prognosis, and these were protective factors of GMA: Regional nodes examined [hazard ratio (HR): 0.98, 95%CI: 0.97-0.98, P < 0.001)] and chemotherapy (HR: 0.62, 95%CI: 0.58-0.66, P < 0.001).

CONCLUSION

The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively. Combining surgery, chemotherapy, and adequate lymph node dissection during surgery can improve patient outcomes.

Unveiling the secrets of gastrointestinal mucous adenocarcinoma survival after surgery with artificial intelligence: A population-based study

BACKGROUND

Research on gastrointestinal mucosal adenocarcinoma (GMA) is limited and controversial, and there is no reference tool for predicting postoperative survival.

AIM

To investigate the prognosis of GMA and develop predictive model.

METHODS

From the Surveillance, Epidemiology, and End Results database, we collected clinical information on patients with GMA. After random sampling, the patients were divided into the discovery (70% of the total, for model training), validation (20%, for model evaluation), and completely blind test cohorts (10%, for further model evaluation). The main assessment metric was the area under the receiver operating characteristic curve (AUC). All collected clinical features were used for Cox proportional hazard regression analysis to determine factors influencing GMA’s prognosis.

RESULTS

This model had an AUC of 0.7433 [95% confidence intervals (95%CI): 0.7424-0.7442] in the discovery cohort, 0.7244 (GMA: 0.7234-0.7254) in the validation cohort, and 0.7388 (95%CI: 0.7378-0.7398) in the test cohort. We packaged it into Windows software for doctors’ use and uploaded it. Mucinous gastric adenocarcinoma had the worst prognosis, and these were protective factors of GMA: Regional nodes examined [hazard ratio (HR): 0.98, 95%CI: 0.97-0.98, P < 0.001)] and chemotherapy (HR: 0.62, 95%CI: 0.58-0.66, P < 0.001).

CONCLUSION

The deep learning-based tool developed can accurately predict the overall survival of patients with GMA postoperatively. Combining surgery, chemotherapy, and adequate lymph node dissection during surgery can improve patient outcomes.

Predictive role of Naples prognostic score for survival in esophageal cancer: A meta-analysis

BACKGROUND

To further clarify the predictive value of pretreatment Naples prognostic score (NPS), calculating based on the serum albumin concentration, total cholesterol level, neutrophil to lymphocyte ratio (NLR) and lymphocyte-to-monocyte ratio (LMR), among esophageal cancer patients based on available evidence.

METHODS

The PubMed, EMBASE, Web of Science and CNKI databases were searched up to December 1, 2023 for relevant studies. Overall survival (OS), progression-free survival (PFS) and cancer-specific survival (CSS) were endpoints and the hazard ratio (HR) with 95% confidence interval (CI) was combined to evaluate the predictive role of NPS for survival. Subgroup analysis based on pathological type and treatment were further conducted.

RESULTS

Ten retrospective studies with 2250 cases were included in our analysis. Pooled results demonstrated that higher pretreatment NPS predicted poorer OS (HR = 2.24, 95% CI: 1.57-3.20, P < .001), PFS (HR = 3.03, 95% CI: 1.84-4.98, P < .001) and CSS (HR = 2.90, 95% CI: 1.80-4.68, P < .001). Then subgroup analysis for the OS and PFS stratified by the pathological type (squamous cell carcinoma vs esophageal cancer) and treatment (surgery vs non-surgery) were further conducted, which showed similar results.

CONCLUSION

Pretreatment NPS is significantly associated with prognosis in esophageal cancer and higher NPS predicts worse survival among patients with esophageal cancer.

Evaluation of immune infiltrate according to the HER2 status in colorectal cancer

BACKGROUND AND AIMS

In colorectal cancer (CRC), HER2 targeting is a promising treatment and immune infiltrate is an important area of research and strategy. Data regarding HER2 status and immune infiltrate are lacking. The aim of this study was to compare the immune infiltrate between HER2 amplified and non-amplified categories in proficient MisMatchRepair (pMMR)/microsatellite stable (MSS) CRC.

METHODS

HER2 immunohistochemistry (IHC) and fluorescence in situ hybridization were performed in a retrospective series of 654 CRC. Lymphocyte infiltrate was analysed by anti-CD3, CD8 and CD4 IHC and evaluated digitally using QuPath software.

RESULTS

Among the 654 CRC, we first observed a decreased CD3+ and CD8+ infiltrate between HER2 amplified (all IHC 3+ except one 2+) and non-amplified HER2 2+ IHC CRC (p = 0.059 and 0.072 respectively). A supplementary analysis of 258 pMMR/MSS CRC from the previous cohort, displaying all the IHC scores (0, 1+, 2+, 3+), showed a lower CD3+ infiltrate between HER2 amplified versus HER2 0 (p = 0.002), 1+ (p = 0.088) and non-amplified 2+ (p = 0.081) IHC cases.

CONCLUSIONS

Our original findings suggest that in pMMR/MSS CRC, the immune infiltrate is reduced in HER2 amplified versus other HER2 categories. These data might be useful for future strategies combining anti-HER2 treatments and immune checkpoint inhibitors and need to be confirmed in larger CRC cohorts.

Integrated analysis reveals FLI1 regulates the tumor immune microenvironment via its cell-type-specific expression and transcriptional regulation of distinct target genes of immune cells in breast cancer

BACKGROUND

Immunotherapy is a practical therapeutic approach in breast cancer (BRCA), and the role of FLI1 in immune regulation has gradually been unveiled. However, the specific role of FLI1 in BRCA was conflicted; thus, additional convincing evidence is needed.

METHODS

We explored the upstream regulation of FLI1 expression via summary data-based Mendelian randomization (SMR) analysis and ncRNA network construction centering on FLI1 using BRCA genome-wide association study (GWAS) summary data with expression quantitative trait loci (eQTLs) and DNA methylation quantitative trait loci (mQTLs) from the blood and a series of in silico analyses, respectively. We illuminated the downstream function of FLI1 in immune regulation by integrating a series of analyses of single-cell RNA sequence data (scRNA-seq).

RESULTS

We verified a causal pathway from FLI1 methylation to FLI1 gene expression to BRCA onset and demonstrated that FLI1 was downregulated in BRCA. FLI1, a transcription factor, served as myeloid and T cells' communication regulator by targeting immune-related ligands and receptor transcription in BRCA tissues. We constructed a ceRNA network centering on FLI1 that consisted of three LncRNAs (CKMT2-AS1, PSMA3-AS1, and DIO3OS) and a miRNA (hsa-miR-324-5p), and the expression of FLI1 was positively related to a series of immune-related markers, including immune cell infiltration, biomarkers of immune cells, and immune checkpoints.

CONCLUSION

Low-methylation-induced or ncRNA-mediated downregulation of FLI1 is associated with poor prognosis, and FLI1 might regulate the tumor immune microenvironment via a cell-type-specific target genes manner in BRCA.

Innovative microwave-assisted biosynthesis of copper oxide nanoparticles loaded with platinum(ii) based complex for halting colon cancer: cellular, molecular, and computational investigations

In the current study, we biosynthesized copper oxide NPs (CuO NPs) utilizing the essential oils extracted from Boswellia carterii oleogum resin, which served as a bioreductant and capping agent with the help of microwave energy. Afterwards, the platinum(ii) based anticancer drug, carboplatin (Cr), was loaded onto the CuO NPs, exploiting the electrostatic interactions forming Cr@CuO NPs. The produced biogenic NPs were then characterized using zeta potential (ZP), high-resolution transmission electron microscopy (HRTEM), X-ray diffraction spectroscopy (XRD), and Fourier transform infrared spectroscopy (FTIR) techniques. In addition, the entrapment efficiency and release profile of the loaded Cr were evaluated. Thereafter, SRB assay was performed, where Cr@CuO NPs demonstrated the highest cytotoxic activity against human colon cancer cells (HCT-116) with an IC50 of 5.17 μg mL-1, which was about 1.6 and 2.2 folds more than that of Cr and CuO NPs. Moreover, the greenly synthesized nanoparticles (Cr@CuO NPs) displayed a satisfactory selectivity index (SI = 6.82), which was far better than the free Cr treatment (SI = 2.23). Regarding the apoptosis assay, the advent of Cr@CuO NPs resulted in an immense increase in the cellular population percentage of HCT-116 cells undergoing both early (16.02%) and late apoptosis (35.66%), significantly surpassing free Cr and CuO NPs. A study of HCT-116 cell cycle kinetics revealed the powerful ability of Cr@CuO NPs to trap cells in the Sub-G1 and G2 phases and impede the G2/M transition. RT-qPCR was utilized for molecular investigations of the pro-apoptotic (Bax and p53) and antiapoptotic genes (Bcl-2). The novel Cr@CuO NPs treatment rose above single Cr or CuO NPs therapy in stimulating the p53-Bax mediated mitochondrial apoptosis. The cellular and molecular biology investigations presented substantial proof of the potentiated anticancer activity of Cr@CuO NPs and the extra benefits that could be obtained from their use.

Comprehensive analysis of EML2 as a prognostic biomarker in colon cancer

BACKGROUND

Echinoderm microtubule-associated protein-like 2 (EML2), a gene located on 19q13.32, is overexpressed in various cancers and has been identified as a prognostic factor. However, the function and carcinogenic mechanism of EML2 in colon cancer is yet to be explored.

METHODS

This study aimed to demonstrate the relationship between EML2 expression and colon cancer using The Cancer Genome Atlas (TCGA) database. The EML2 expression, including GSE33113 and GSE39923, was validated in colon cancer in the Gene Expression Omnibus (GEO) database. The Receiver Operating Characteristic (ROC) curves were used to assess the feasibility of EML2 as a distinguishing factor from the area under the curve (AUC) scores. In addition, Cox regression and logistic regression analyses were conducted to evaluate the factors linked to the prognosis of colon cancer. Moreover, the STRING tool was used to establish the EML2 binding protein network. The enrichment analysis cluster Profiler of the R package was utilized to investigate the function of EML2. The relationship between the immune infiltration and EML2 expression level in colon cancer was investigated by the R package Gene Set Variation Analysis (GSVA) and the single sample Gene Set Enrichment Analysis (ssGSEA) method in the Tumor Immune Estimation Resource (TIMER) database.

RESULTS

Pan-cancer data analysis revealed that EML2 expression was higher in most cancers, including colon cancer. This outcome was in line with the findings of the GEO database. The ROC curve demonstrated that EML2 can serve as a diagnostic biomarker for colon cancer (AUC = 0.738). High EML2 expression was associated with poorer overall survival (OS; P = 0.004). Moreover, the results of the enrichment and immune infiltration analysis revealed that high EML2 expression correlated with regulation of the infiltration level of GTPase binding and some immune cell types like NK cells and NK CD56 bright cells.

CONCLUSION

The findings revealed that colon cancer tissues had a higher EML2 expression than normal colon epithelial tissues. This phenomenon was significantly associated with poor prognosis and altered immune cell infiltration. Consequently, EML2 has shown the capacity to serve as a prognostic biomarker for patients diagnosed with colon cancer.

CD4 levels and NSCLC metastasis: the benefits of maintaining moderate levels

OBJECTIVES

Prior researches indicate that peripheral blood CD4 levels have an inverse correlation with distant tumor metastasis in non-small cell lung cancer (NSCLC). However, the linear relationship between CD4 and distant metastasis lacks clarity. Hence, the objective of this study was to ascertain the linear relationship between CD4 and distant metastasis in NSCLC patients.

METHODS

This retrospective study analyzed clinical and laboratory data of NSCLC patients between March 2016 and July 2022 at the Cancer Hospital of Anhui University of Technology. The study first applied a generalized summation model and smoothing curve fitting to determine if there was a linear relationship between CD4 and NSCLC metastasis. Secondarily, univariate logistic analysis and multiple linear regression were used to analyze the odds ratio (OR) of CD4 as a continuous variable, dichotomous variable, and trichotomous variable when predicting NSCLC metastasis. In addition, stratified and subgroup analyses were conducted to assess the reliability of CD4 in different NSCLC patient populations.

RESULTS

The study included a total of 213 NSCLC patients, among which 122 had distant metastasis and 91 had no metastasis. The smoothing curve fitting analysis revealed a U-shaped relationship between CD4 and NSCLC metastasis with a threshold effect. The univariate logistic analysis indicated that continuous CD4 expression was not significantly associated with NSCLC metastasis (P = 0.051); however, high levels of CD4 expression (≥ 35.06%) were found to be a protective factor against NSCLC metastasis when CD4+ T was a dichotomous variable (OR = 0.49, P = 0.010). Furthermore, multivariate linear regression models showed that low (< 32%) or high levels (> 44%) of CD4 significantly increased the risk of NSCLC metastasis compared to medium levels (32-44%) when CD4+ T was trichotomized. The significance was maintained in stratified analysis in relation to age, sex, type of pathology, smoke, PS, and T stage. CD4 levels were U-shaped in relation to different sites of distant metastases (bone, brain, liver), but not with lung metastases.

CONCLUSIONS

A threshold effect is shown to exist between the peripheral blood CD4 and distant metastasis in NSCLC patients. It was revealed that the risk of distant metastasis is lower when CD4 is maintained between 32 and 44%, whereas low (< 32%) or high (> 44) levels of CD4 are associated with an increased risk of distant metastasis in NSCLC patients.

Propolis Has an Anticancer Effect on Early Stage Colorectal Cancer by Affecting Epithelial Differentiation and Gut Immunity in the Tumor Microenvironment

Colorectal cancer (CRC) is one of the most common cancers and is the second leading cause of cancer-related death in the world. Due to the westernization of diets, young patients with CRC are often diagnosed at advanced stages with an associated poor prognosis. Improved lifestyle choices are one way to minimize CRC risk. Among diet choices is the inclusion of bee propolis, long recognized as a health supplement with anticancer activities. Understanding the effect of propolis on the gut environment is worth exploring, and especially its associated intratumoral immune changes and its anticancer effect on the occurrence and development of CRC. In this study, early stage CRC was induced with 1,2-dimethylhydrazine (DMH) and dextran sulfate sodium (DSS) for one month in an animal model, without and with propolis administration. The phenotypes of early stage CRC were evaluated by X-ray microcomputed tomography and histologic examination. The gut immunity of the tumor microenvironment was assessed by immunohistochemical staining for tumor-infiltrating lymphocytes (TILs) and further comparative quantification. We found that the characteristics of the CRC mice, including the body weight, tumor loading, and tumor dimensions, were significantly changed due to propolis administration. With further propolis administration, the CRC tissues of DMH/DSS-treated mice showed decreased cytokeratin 20 levels, a marker for intestinal epithelium differentiation. Additionally, the signal intensity and density of CD3+ and CD4+ TILs were significantly increased and fewer forkhead box protein P3 (FOXP3) lymphocytes were observed in the lamina propria. In conclusion, we found that propolis, a natural supplement, potentially prevented CRC progression by increasing CD3+ and CD4+ TILs and reducing FOXP3 lymphocytes in the tumor microenvironment of early stage CRC. Our study could suggest a promising role for propolis in complementary medicine as a food supplement to decrease or prevent CRC progression.

Deciphering the mechanism of Peptostreptococcus anaerobius-induced chemoresistance in colorectal cancer: the important roles of MDSC recruitment and EMT activation

Peptostreptococcus anaerobius (P. anaerobius, PA) in intestinal flora of patients with colorectal cancer (CRC) are associated with poor prognosis. Studies have shown that P. anaerobius could promote colorectal carcinogenesis and progression, but whether P. anaerobius could induce chemoresistance of colorectal cancer has not been clarified. Here, both in vitro and in vivo experiments showed that P. anaerobius specifically colonized the CRC lesion and enhanced chemoresistance of colorectal cancer to oxaliplatin by recruiting myeloid-derived suppressor cells (MDSCs) into the tumor microenvironment. Furthermore, this study revealed that it was the increased secretion of IL-23 by MDSCs that subsequently facilitated the epithelial-mesenchymal transition (EMT) of tumor cells to induce chemoresistance of CRC by activating the Stat3-EMT pathway. Our results highlight that targeting P. anaerobius might be a novel therapeutic strategy to overcome chemoresistance in the treatment of CRC.

Machine learning-based integration develops a metabolism-derived consensus model for improving immunotherapy in pancreatic cancer

BACKGROUND

Pancreatic cancer (PAC) is one of the most malignant cancer types and immunotherapy has emerged as a promising treatment option. PAC cells undergo metabolic reprogramming, which is thought to modulate the tumor microenvironment (TME) and affect immunotherapy outcomes. However, the metabolic landscape of PAC and its association with the TME remains largely unexplored.

METHODS

We characterized the metabolic landscape of PAC based on 112 metabolic pathways and constructed a novel metabolism-related signature (MBS) using data from 1,188 patients with PAC. We evaluated the predictive performance of MBS for immunotherapy outcomes in 11 immunotherapy cohorts from both bulk-RNA and single-cell perspectives. We validated our results using immunohistochemistry, western blotting, colony-formation assays, and an in-house cohort.

RESULTS

MBS was found to be negatively associated with antitumor immunity, while positively correlated with cancer stemness, intratumoral heterogeneity, and immune resistant pathways. Notably, MBS outperformed other acknowledged signatures for predicting immunotherapy response in multiple immunotherapy cohorts. Additionally, MBS was a powerful and robust biomarker for predicting prognosis compared with 66 published signatures. Further, we identified dasatinib and epothilone B as potential therapeutic options for MBS-high patients, which were validated through experiments.

CONCLUSIONS

Our study provides insights into the mechanisms of immunotherapy resistance in PAC and introduces MBS as a robust metabolism-based indicator for predicting response to immunotherapy and prognosis in patients with PAC. These findings have significant implications for the development of personalized treatment strategies in patients with PAC and highlight the importance of considering metabolic pathways and immune infiltration in TME regulation.

Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms

Background: Colorectal cancer (CRC) is one of the most prevalent cancer types globally. A survival paradox exists due to the inherent heterogeneity in stage II/III CRC tumor biology. Ferroptosis is closely related to the progression of tumors, and ferroptosis-related genes can be used as a novel biomarker in predicting cancer prognosis. Methods: Ferroptosis-related genes were retrieved from the FerrDb and KEGG databases. A total of 1,397 samples were enrolled in our study from nine independent datasets, four of which were integrated as the training dataset to train and construct the model, and validated in the remaining datasets. We developed a machine learning framework with 83 combinations of 10 algorithms based on 10-fold cross-validation (CV) or bootstrap resampling algorithm to identify the most robust and stable model. C-indice and ROC analysis were performed to gauge its predictive accuracy and discrimination capabilities. Survival analysis was conducted followed by univariate and multivariate Cox regression analyses to evaluate the performance of identified signature. Results: The ferroptosis-related gene (FRG) signature was identified by the combination of Lasso and plsRcox and composed of 23 genes. The FRG signature presented better performance than common clinicopathological features (e.g., age and stage), molecular characteristics (e.g., BRAF mutation and microsatellite instability) and several published signatures in predicting the prognosis of the CRC. The signature was further stratified into a high-risk group and low-risk subgroup, where a high FRG signature indicated poor prognosis among all collected datasets. Sensitivity analysis showed the FRG signature remained a significant prognostic factor. Finally, we have developed a nomogram and a decision tree to enhance prognosis evaluation. Conclusion: The FRG signature enabled the accurate selection of high-risk stage II/III CRC population and helped optimize precision treatment to improve their clinical outcomes.

Immune gene signatures as prognostic criteria for cancer patients

Recently, the possibility of using immune gene signatures (IGSs) has been considered as a novel prognostic tool for numerous cancer types. State-of-the-art methods of genomic, transcriptomic, and protein analysis have allowed the identification of a number of immune signatures correlated to disease outcome. The major adaptive and innate immune components are the T lymphocytes and macrophages, respectively. Herein, we collected essential data on IGSs consisting of subsets of T cells and tumor-associated macrophages and indicating cancer patient outcomes. We discuss factors that can introduce errors in the recognition of immune cell types and explain why the significance of immune signatures can be interpreted with uncertainty. The unidirectional functions of cell types should be entirely addressed in the signatures constructed by the combination of innate and adaptive immune cells. The state of the antitumor immune response is the key basis for IGSs and should be considered in gene signature construction. We also analyzed immune signatures for the prediction of immunotherapy response. Finally, we attempted to explain the present-day limitations in the use of immune signatures as robust criteria for prognosis.

m5C regulator-mediated methylation modification phenotypes characterized by distinct tumor microenvironment immune heterogenicity in colorectal cancer

The RNA 5-methylcytosine (m5C) modification has been demonstrated to be an important epigenetic regulator and to impact colorectal cancer (CRC) progression. However, the potential roles of m5C modification in immune cell infiltration in the CRC tumor microenvironment (TME) remain unknown. The m5C modification phenotypes were comprehensively evaluated based on 14 m5C regulators in a meta-CRC cohort of 1792 patients and systematically correlated with the m5C modification phenotypes, immune cell infiltration characteristics and known biological processes. The m5Cscore model was constructed by principal component analysis (PCA) algorithms to quantify the m5C modification phenotypes of individual CRC samples and was used to predict the immunotherapy response. We identified three m5C modification phenotypes associated with distinct clinical outcomes and biological processes among the 1792 meta-CRC patients. Three phenotypes with a highly consistent TME landscape and characteristics were revealed: immune excluded, immune desert and immune inflammation. The meta-CRC patients were divided into high and low m5Cscore subgroups based on the m5Cscore. The m5Cscore was confirmed to have a negative correlation with infiltrating immune cells and PD-L1 expression and a positive correlation with tumor mutation burden (TMB), mutation rate and microsatellite instability (MSI) score. Moreover, patients in the low m5Cscore group had better immunotherapy responses and significant durable survival benefits in independent anti-PD-1/L1 immunotherapy cohorts for the immune checkpoint inhibitor (ICI) therapeutic strategy. This study revealed that m5C modification plays a crucial role in TME composition and complexity. Comprehensive evaluation of the m5C modification phenotypes of individual patients will enhance our understanding of TME characteristics and promote the application of more appropriate and personalized treatment strategies.

Exploring Cancer Dependency Map genes and immune subtypes in colon cancer, in which TIGD1 contributes to colon cancer progression

BACKGROUND

Tumour-dependent genes identified in CRISPR-Cas9 screens have been widely reported in Cancer Dependency Maps (CDMs). CDM-derived tumour-dependent genes play an important role in tumorigenesis and progression; however, they have not been investigated in colon cancer (CC).

METHODS

CDM genes overexpressed in CC were identified from the TCGA-COAD dataset and CDM platform. A CDM signature and prognostic nomogram were constructed by Lasso Cox regression and multivariate Cox analyses. A weighted correlation network analysis (WGCNA) and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. A comprehensive investigation was performed between the two subtypes and immune regulation, the immune microenvironment and the impact of immunotherapy.

RESULTS

First, 1304 overexpressed CDM genes were identified. Then, a CDM signature with five cancer-dependent genes (MMS19, NOP14, POLRMT, SNAPC5 and TIGD1) and a prognostic nomogram were constructed, and they demonstrated robust predictive performance and a close relationship with clinical characteristics in different CC datasets. Patients with high CDM risk scores showed worse survival outcome and weaker response to chemotherapy. Additionally, TIGD1 genes were oncogenes that affected the CC cell cycle, according to cell functional experiments that involved the suppression of the TIGD1 gene. Furthermore, WGCNA and consensus clustering were used to define coexpressed genes with CDM risk scores and to determine two new immune subtypes. Finally, systematic investigations were conducted with the relationship between the CDM subtypes and immune regulation.

CONCLUSIONS

This study constructed a CDM signature consisting of five risk genes that predict survival in CC patients. In addition, the immune subtypes provided valuable insights into immunotherapy for CC patients. TIGD1, as an oncogene, is independent prognostic factors for CC, and contributes to CC progression.

Riskscore Model Based on Oxidative Stress-Related Genes May Facilitate the Prognosis Evaluation for Patients With Colon Cancer

INTRODUCTION

This study aims to identify the oxidative stress-related genes (OSRGs) with prognostic value and develop a riskscore model for prognosis evaluation in colon cancer.

METHODS

The transcriptome data and corresponding clinical information about colon cancer were extracted from The Cancer Genome Atlas database. Differentially expressed OSRGs and transcription factors (TFs) were identified between the normal and tumor samples. A riskscore model was established with OSRGs filtered from Cox regression analysis. This riskscore model was appraised by Kaplan-Meier plot, receiver operating characteristic curve, and Cox regression analysis. The clinical relevance of riskscore and its association with immune cell infiltration were also evaluated.

RESULTS

A total of 307 differentially expressed OSRGs and 64 differential TFs were identified. A TF-OSRG regulatory network was constructed in Cytoscape software. A riskscore model was established based on 17 OSRGs with independent prognostic value. This riskscore model could separate the patients into low-risk and high-risk groups. It also had good predictive ability, with an area under the curve = 0.8. In multivariate Cox regression analysis, age, T stage, and riskscore were identified as independent risk factors in colon cancer. Riskscore was significantly correlated with T stage, N stage, and immune cell infiltration.

DISCUSSION

We established a useful riskscore model with 17 OSRGs for prognosticating the overall survival in patients with colon cancer. This study provides a new insight into the clinical utility of OSRG-based riskscore model, which will hopefully facilitate the prognosis evaluation of patients with colon cancer.

Comprehensive analysis of novel cancer prediction genes and tumor microenvironment infiltration in colon cancer

BACKGROUND

Colon cancer with high incidence and mortality is a severe public health problem. As an emerging therapy, immunotherapy has played an active clinical role in tumor treatment, but only a small number of patients respond.

METHODS

By univariate Cox regression analysis of 165 novel cancer prediction genes (NCPGs), 29 NCPGs related to prognosis were screened. Based on these 29 NCPGs and 336 differentially expressed genes, we constructed two colon cancer subgroups and three gene clusters and analyzed prognosis, activation pathways, and immune infiltration characteristics under various modification patterns. Then each patient was scored and divided into high or low NCPG_score groups. A comprehensive evaluation between NCPG_score and clinical characteristics, tumor microenvironment (TME), tumor somatic mutations, and the potential for immunotherapy was conducted.

RESULTS

Patients with high NCPG_score were characterized by high tumor mutation burden and high microsatellite instability and were more suitable for immunotherapy.

CONCLUSIONS

This study screened 29 NCPGs as independent prognostic markers in colon cancer patients, demonstrating their TME, clinicopathological features, and potential roles in immunotherapy, helping to assess prognosis and guiding more personalized immunotherapy.

APC mutation correlated with poor response of immunotherapy in colon cancer

OBJECTIVE

APC (adenomatous polyposis coli) gene mutation is a central initialization in colon cancer tumorigenesis. However, the connection between APC gene mutation and immunotherapy efficacy for colon cancer remains unknown. This study aimed to explore the impact of APC mutation on immunotherapy efficacy for colon cancer.

METHODS

Colon cancer data from The Cancer Genome Atlas (TCGA) and Memorial Sloan Kettering Cancer Center (MSKCC) were used for the combined analysis. Survival analysis was performed to evaluate the association between APC mutation and immunotherapy efficacy in colon cancer patients. The expressions of immune check point molecules, tumor mutation burden (TMB), CpG methylation level, tumor purity (TP), microsatellite instability (MSI) status and tumor-infiltrating lymphocyte (TIL) in the two APC status were compared to evaluate the associations between APC mutation and immunotherapy efficacy indicators. Gene set enrichment analysis (GSEA) was performed to identify signaling pathways related to APC mutation.

RESULTS

APC was the most frequently mutated gene in colon cancer. The survival analysis demonstrated that APC mutation was correlated with a worse immunotherapy outcome. APC mutation was associated with lower TMB, lower expression of immune check point molecules (PD-1/PD-L1/PD-L2), higher TP, lower MSI-High proportion and less CD8 + T cells and follicular helper T cells infiltration. GSEA indicated that APC mutation up-regulated mismatch repair pathway, which may play a negative role in evoking an antitumor immune response.

CONCLUSION

APC mutation is associated with worse immunotherapy outcome and inhibition of antitumor immunity. It can be used as a negative biomarker to predict immunotherapy response.

FHL1 as a novel prognostic biomarker and correlation with immune infiltration levels in lung adenocarcinoma

Aim: We aimed to examine the effect of FHL1 in the diagnosis and prognosis of non-small-cell lung cancer and its relationship with tumor-infiltrating immune cells. Methods: FHL1 expression status and influence on clinical characteristics, diagnosis and prognosis in non-small-cell lung cancer were assessed. Interaction networks of FHL1 were revealed, and a correlation analysis between FHL1 expression and tumor immunity was performed. Results: FHL1 expression was significantly lower in tumors, and downregulated FHL1 predicted a worse prognosis for lung adenocarcinoma. FHL1 expression was correlated with tumor-infiltrating immune cells, immune checkpoints and chemokine levels. Conclusion: FHL1 is a powerful biomarker to evaluate the diagnosis and prognosis and immune infiltration level of lung adenocarcinoma.

Construction of a DDR-related signature for predicting of prognosis in metastatic colorectal carcinoma

Background

Colorectal cancer (CRC) is the third most prevalent malignancy and the one of most lethal cancer. Metastatic CRC (mCRC) is the third most common cause of cancer deaths worldwide. DNA damage response (DDR) genes are closely associated with the tumorigenesis and development of CRC. In this study, we aimed to construct a DDR-related gene signature for predicting the prognosis of mCRC patients.

Methods

The gene expression and corresponding clinical information data of CRC/mCRC patients were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. A prognostic model was obtained and termed DDRScore by the multivariate Cox proportional hazards regression in the patients with mCRC. The Kaplan-Meier (K-M) and Receiver Operating Characteristic (ROC) curves were employed to validate the predictive ability of the prognostic model. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed for patients between the high-DDRscore and low-DDRscore groups.

Results

We constructed a prognostic model consisting of four DDR-related genes (EME2, MSH4, MLH3, and SPO11). Survival analysis showed that patients in the high-DDRscore group had a significantly worse OS than those in the low-DDRscore group. The area under the curve (AUC) value of the ROC curve of the predictive model is 0.763 in the training cohort GSE72970, 0.659 in the stage III/IV colorectal cancer (CRC) patients from The Cancer Genome Atlas (TCGA) data portal, and 0.639 in another validation cohort GSE39582, respectively. GSEA functional analysis revealed that the most significantly enriched pathways focused on nucleotide excision repair, base excision repair, homologous recombination, cytokine receptor interaction, chemokine signal pathway, cell adhesion molecules cams, ECM-receptor interaction, and focal adhesion.

Conclusion

The DDRscore was identified as an independent prognostic and therapy response predictor, and the DDR-related genes may be potential diagnosis or prognosis biomarkers for mCRC patients.

A signature of immune-related genes correlating with clinical prognosis and immune microenvironment in sepsis

BACKGROUND

Immune-related genes (IRGs) remain poorly understood in their function in the onset and progression of sepsis.

METHODS

GSE65682 was obtained from the Gene Expression Omnibus database. The IRGs associated with survival were screened for subsequent modeling using univariate Cox regression analysis and least absolute shrinkage and selection operator in the training cohort. Then, we assessed the reliability of the 7 IRGs signature's independent predictive value in the training and validation cohorts following the creation of a signature applying multivariable Cox regression analysis. After that, we utilized the E-MTAB-4451 external dataset in order to do an independent validation of the prognostic signature. Finally, the CIBERSORT algorithm and single-sample gene set enrichment analysis was utilized to investigate and characterize the properties of the immune microenvironment.

RESULTS

Based on 7 IRGs signature, patients could be separated into low-risk and high-risk groups. Patients in the low-risk group had a remarkably increased 28-day survival compared to those in the high-risk group (P < 0.001). In multivariable Cox regression analyses, the risk score calculated by this signature was an independent predictor of 28-day survival (P < 0.001). The signature's predictive ability was confirmed by receiver operating characteristic curve analysis with the area under the curve reaching 0.876 (95% confidence interval 0.793-0.946). Moreover, both the validation set and the external dataset demonstrated that the signature had strong clinical prediction performance. In addition, patients in the high-risk group were characterized by a decreased neutrophil count and by reduced inflammation-promoting function.

CONCLUSION

We developed a 7 IRGs signature as a novel prognostic marker for predicting sepsis patients' 28-day survival, indicating possibilities for individualized reasonable resource distribution of intensive care unit.

Identification of an Immune-Related Gene Signature Associated with Prognosis and Tumor Microenvironment in Esophageal Cancer

Background

Esophageal cancer (EC) is a common malignant tumor of the digestive system with high mortality and morbidity. Current evidence suggests that immune cells and molecules regulate the initiation and progression of EC. Accordingly, it is necessary to identify immune-related genes (IRGs) affecting the biological behaviors and microenvironmental characteristics of EC.

Methods

Bioinformatics methods, including differential expression analysis, Cox regression, and immune infiltration prediction, were conducted using R software to analyze the Gene Expression Omnibus (GEO) dataset. The Cancer Genome Atlas (TCGA) cohort was used to validate the prognostic signature. Patients were stratified into high- and low-risk groups for further analyses, including functional enrichment, immune infiltration, checkpoint relevance, clinicopathological characteristics, and therapeutic sensitivity analyses.

Results

A prognostic signature was established based on 21 IRGs (S100A7, S100A7A, LCN1, CR2, STAT4, GAST, ANGPTL5, TRAV39, F2RL2, PGLYRP3, KLRD1, TRIM36, PDGFA, SLPI, PCSK2, APLN, TICAM1, ITPR3, MAPK9, GATA4, and PLAU). Compared with high-risk patients, better overall survival rates and clinicopathological characteristics were found in low-risk patients. The areas under the curve of the two cohorts were 0.885 and 0.718, respectively. Higher proportions of resting CD4⁺ memory T lymphocytes, M2 macrophages, and resting dendritic cells and lower proportions of follicular helper T lymphocytes, plasma cells, and neutrophils were found in the high-risk tumors. Moreover, the high-risk group showed higher expression of CD44 and TNFSF4, lower expression of PDCD1 and CD40, and higher TIDE scores, suggesting they may respond poorly to immunotherapy. High-risk patients responded better to chemotherapeutic agents such as docetaxel, doxorubicin, and gemcitabine. Furthermore, IRGs associated with tumor progression, including PDGFA, ITPR3, SLPI, TICAM1, and GATA4, were identified.

Conclusion

Our immune-related signature yielded reliable value in evaluating the prognosis, microenvironmental characteristics, and therapeutic sensitivity of EC and may help with the precise treatment of this patient population.

A pretreatment transcriptomic signature that predicts outcomes of immunotherapy in melanoma

Identifying indicators of immunotherapy response are key to clinical treatment decisions. To date, immunotherapy is most widely used in melanoma because of its higher tumor mutation burden compared to other cancer types. However, less than half of melanoma patients can benefit from immune checkpoint inhibitor (ICI) therapy. For this reason, we deciphered pretreatment transcriptomes across a cohort of melanoma patients receiving anti-PD-1 or CTLA-4 alone (sICI) or in combination (cICI). We developed a two-gene signature that could predict the curative effect of ICI in melanoma by using the LASSO method. The pre-ICI signature displayed an equally competitive predictive power as the post-ICI irRECIST assessment that could offer clues regarding long-term ICI therapy response and facilitate risk stratification and treatment strategies.

Pan-cancer analysis of FBXW family with potential implications in prognosis and immune infiltration

Background

The F-box and WD repeat domain containing (FBXW) family of SCF E3 complexes has 10 members that are responsible for ubiquitination and degradation of substrate proteins involved in cell cycle regulation and tumorigenesis. Among them, FBXW1 (also called b-TrCP1/BTRC) and FBXW7 are the central proteins in this category. However, there is still a lack of elaborate exploration of the contribution of FBXW family members, especially FBXW1 and FBXW7, in various tumor types.

Methods

In this present study, we preliminarily analyzed the genetic structure characteristics of the FBXW family, and systematically investigated their expression patterns and clinical correlations based on the TCGA pan-cancer data. Survival analysis of FBXWs was also conducted through the Kaplan-Meier method. In addition, we assessed their immune infiltration level through immune-related algorithms like Timer and xCell.

Results

There were obvious genetic heterogeneity and different clinical traits in FBXW family members. Moreover, we found that FBXW family genes may be useful in predicting prognosis and therapeutic efficacy using survival analysis. In addition, the immune infiltration of FBXW family was also clearly illustrated in this study. The results showed these genes were closely involved in immune components such as immune score, immune subtypes, tumor-infiltrating lymphocytes and immune checkpoints. Notedly, FBXW1 as an oncogene and FBXW7 as a tumor suppressor gene also show opposite relationships on immune cells.

Conclusion

Our results provided valuable strategies to guide the therapeutic orientation concerning the role of FBXW family genes in cancer.

Identification of necroptosis-related subtypes, development of a novel signature, and characterization of immune infiltration in colorectal cancer

Introduction

Necroptosis, a type of programmed cell death, has recently been extensively studied as an important pathway regulating tumor development, metastasis, and immunity. However, the expression patterns of necroptosis-related genes (NRGs) in colorectal cancer (CRC) and their potential roles in the tumor microenvironment (TME) have not been elucidated.

Methods

We explored the expression patterns of NRGs in 1247 colorectal cancer samples from genetics and transcriptional perspective. Based on a consensus clustering algorithm, we identified NRG molecular subtypes and gene subtypes, respectively. Furthermore, we constructed a necroptosis-related signature for predicting overall survival time and verified the predictive ability of the model. Using the ESTIMATE, CIBERSORT, and ssGSEA algorithms, we assessed the association between the above subtypes, scores and immune infiltration.

Results

Most NRGs were differentially expressed between CRC tissues and normal tissues. We found that distinct subtypes exhibited different NRGs expression, patients' prognosis, immune checkpoint gene expression, and immune infiltration characteristics. The scores calculated from the necroptosis-related signature can be used to classify patients into high-risk and low-risk groups, with the high-risk group corresponding to reduced immune cell infiltration and immune function, and a greater risk of immune dysfunction and immune escape.

Discussion

Our comprehensive analysis of NRGs in CRC demonstrated their potential role in clinicopathological features, prognosis, and immune infiltration in the TME. These findings help us deepen our understanding of NRGs and the tumor microenvironment landscape, and lay a foundation for effectively assessing patient outcomes and promoting more effective immunotherapy.

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.

Comprehensive analysis of the immune implication of FABP4 in colon adenocarcinoma

Background

Fatty acid-binding protein 4 (FABP4) has been reported to be associated with tumor progress and poor prognosis in various cancers. However, the relationship between FABP4 expression and tumor immunity in colon adenocarcinoma (COAD) is still poorly understood.

Methods

FABP4 mRNA expression was analyzed using The Cancer Genome Atlas (TCGA)-COAD data. FABP4 protein staining was performed by immunohistochemistry (IHC) staining in our 10 paired COAD samples and corresponding adjacent noncancerous tissues. The association between FABP4 and immune cell infiltration was evaluated by Tumor Immune Estimation Resource (TIMER) database. FABP4 coexpressed genes were identified based on Cancer Cell Line Encyclopedia (CCLE) database, which were employed for further enrichment analysis. FABP4 related immunomodulators was identified by Tumor and Immune System Interaction Database (TISIDB) database, and a prognostic risk signature was constructed based on FABP4-related immunomodulators using stepwise Cox regression analysis. A nomogram consists of FABP4 related immunomodulators signature and clinical parameters was developed to predict the overall survival (OS).

Results

In TCGA data, we found that the decreased FABP4 mRNA expression in COAD samples compared with normal samples, and low FABP4 mRNA expression was associated with B cells, CD4+ T cells, CD8+ T cells, myeloid dendritic cells, macrophages, and neutrophils. In our 10 paired samples, the protein levels of COAD were lower in all COAD tissues than in their adjacent noncancerous tissues. Functional enrichment analysis revealed that FABP4 coexpressed genes were mostly enriched in immune-related pathways. Based on 54 FABP4-related immunomodulators, a 2-gene FABP4-related prognostic risk signature was developed, and the signature stratified the patients into the high-risk and low-risk groups with statistically different survival outcomes. The Nomogram consists of the prognostic signature and clinical parameters had a certain predictability for prognosis of COAD patients.

Conclusion

These findings suggest that FABP4 is associated with 2-gene immune signature which also correlate with the prognosis of COAD patients.

Circulating Tumor DNA Allele Fraction: A Candidate Biological Signal for Multicancer Early Detection Tests to Assess the Clinical Significance of Cancers

Current imaging-based cancer screening approaches provide useful but limited prognostic information. Complementary to existing screening tests, cell-free DNA-based multicancer early detection (MCED) tests account for cancer biology [manifested through circulating tumor allele fraction (cTAF)], which could inform prognosis and help assess the cancer's clinical significance. This review discusses the factors affecting circulating tumor DNA (ctDNA) levels and cTAF, and their correlation with the cancer's clinical significance. Furthermore, it discusses the influence of cTAF on MCED test performance, which could help inform prognosis. Clinically significant cancers show higher ctDNA levels quantified by cTAF than indolent phenotype cancers within each stage. This is because more frequent mitosis and cell death combined with increased trafficking of cell-free DNA into circulation leads to greater vascularization and depth of tumor invasion. cTAF has been correlated with biomarkers for cancer aggressiveness and overall survival; cancers with lower cTAF had better survival when compared with cancers as determined by the higher cTAF and Surveillance, Epidemiology, and End Results-based survival for that cancer type at each stage. MCED-detected cancers in case-control studies had comparable survival to Surveillance, Epidemiology, and End Results-based survival at each stage. Because many MCED tests use ctDNA as an analyte, cTAF could provide a common metric to compare performance. The prognostic value of cTAF may allow MCED tests to preferentially detect clinically significant cancers at early stages when outcomes are favorable and this may avoid overdiagnosis.

Identification of immune and stromal cell infiltration-related gene signature for prognosis prediction in acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is a common and life-threatening hematologic malignancy, its occurrence and progression are closely related to immune/stromal cell infiltration in the bone marrow (BM) microenvironment. However, no studies have described an immune/stromal cell infiltration-related gene (ISCIRG)-based prognostic signature for ALL. A total of 444 patients involving 437 bulk and 7 single-cell RNA-seq datasets were included in this study. Eligible datasets were searched and reviewed from the database of TCGA, TARGET project and GEO. Then an integrated bioinformatics analysis was performed to select optimal prognosis-related genes from ISCIRGs, construct a nomogram model for predicting prognosis, and assess the predictive power. After LASSO and multivariate Cox regression analyses, a seven ISCIRGs-based signature was proved to be able to significantly stratify patients into high- and low-risk groups in terms of OS. The seven genes were confirmed that directly related to the composition and status of immune/stromal cells in BM microenvironment by analyzing bulk and single-cell RNA-seq datasets. The calibration plot showed that the predicted results of the nomogram were consistent with the actual observation results of training/validation cohort. This study offers a reference for future research regarding the role of ISCIRGs in ALL and the clinical care of patients.

m6A Regulator-Based Exosomal Gene Methylation Modification Patterns Identify Distinct Microenvironment Characterization and Predict Immunotherapeutic Responses in Colon Cancer

Recent studies have highlighted the biological significance of exosomes and m6A modifications in immunity. Nonetheless, it remains unclear whether the m6A modification gene in exosomes of body fluid has potential roles in the tumor microenvironment (TME). Herein, we identified three different m6A-related exosomal gene modification patterns based on 59 m6A-related exosomal genes, which instructed distinguishing characteristics of TME in colon cancer (CC). We demonstrated that these patterns could predict the stage of tumor inflammation, subtypes, genetic variation, and patient prognosis. Furthermore, we developed a scoring mode—m6A-related exosomal gene score (MREGS)—by detecting the level of m6A modification in exosomes to classify immune phenotypes. Low MREGS, characterized by prominent survival and immune activation, was linked to a better response to anti-PDL1 immunotherapy. In contrast, the higher MREGS group displayed remarkable stromal activation, high activity of innate immunocytes, and a lower survival rate. Hence, this work provides a novel approach for evaluating TME cell infiltration in colon cancer and guiding more effective immunotherapy strategies.

Analysis of the Prognostic Significance and Immune Infiltration of the Amino Acid Metabolism-Related Genes in Colon Adenocarcinoma

Amino acid metabolization is verified to be a part in the progression of cancer. However, genes related to the amino acid metabolism have not been identified in colon adenocarcinoma (COAD). A systematic prognostic model of COAD becomes a pressing need. Among genes related to the amino acid metabolism, RIMKLB, ASPG, TH, MTAP, AZIN2, PSMB2, HDC, ACMSD, and PSMA8 were identified to construct a risk model. Kaplan–Meier (K–M) analyses demonstrated that the high-risk group achieved a poor prognosis. Area under the respective ROC (AUC) values indicated the robustness of the model. To highlight its clinical value, multivariate Cox was used to obtain the optimal variables to construct a nomogram. A higher tumor mutation burden was observed in the high-risk group. However, the low-risk group had a stronger immune infiltration. Seven molecular subtypes were found by consensus cluster. Twenty-two hub genes were identified related to the ESTIMATE score using WGCNA. In brief, our research constructed a stable prognostic model related to the amino acid metabolism in COAD, revealing its connection to the immune microenvironment. The model guided the outcome of COAD and the direction of immunotherapy.

Identification of Endoplasmic Reticulum Stress-Related Subtypes, Infiltration Analysis of Tumor Microenvironment, and Construction of a Prognostic Model in Colorectal Cancer

Recently, endoplasmic reticulum (ER) stress has been shown to influence tumor progression and immune cell function in the tumor microenvironment (TME). However, the underlying role of ER stress-related gene patterns in colorectal cancer (CRC) development remains unclear. We analyzed the ER stress-related gene patterns in 884 patients with CRC from the Gene Expression Omnibus database and evaluated the cell-infiltrating patterns in the TME. Two ER stress-related patterns were identified in patients with CRC that had distinct cell-infiltrating patterns in the TME and clinical characteristics. A risk score and nomogram based on 14 screened prognosis-correlated genes was built and validated to predict patient survival. Patients with a higher risk score were shown to have an unfavorable prognosis, and the risk score was associated with cell infiltration and drug sensitivity. Furthermore, spatial transcriptomics data were utilized to explore ER stress-related gene patterns in CRC tissues, and it was shown that ER stress phenotype involves in the formation of the immunosuppressive TME. This study demonstrated that ER stress-related gene patterns play a role in influencing the TME and predicting prognosis. These analyses of ER stress in the TME of CRC might deepen our understanding of CRC progression and immune escape and provide novel insights into therapeutic strategies.

Integrated multi-omics characterization of KRAS mutant colorectal cancer

KRAS mutation is the most frequent oncogenic aberration in colorectal cancer (CRC). The molecular mechanism and clinical implications of KRAS mutation in CRC remain unclear and show high heterogeneity within these tumors. Methods: We harnessed the multi-omics data (genomic, transcriptomic, proteomic, and phosphoproteomic etc.) of KRAS-mutant CRC tumors and performed unsupervised clustering to identify proteomics-based subgroups and molecular characterization. Results: In-depth analysis of the tumor microenvironment by single-cell transcriptomic revealed the cellular landscape of KRAS-mutant CRC tumors and identified the specific cell subsets with KRAS mutation. Integrated multi-omics analyses separated the KRAS-mutant tumors into two distinct molecular subtypes, termed KRAS-M1 (KM1) and KRAS-M2 (KM2). The two subtypes had a similar distribution of mutated residues in KRAS (G12D/V/C etc.) but were characterized by distinct features in terms of prognosis, genetic alterations, microenvironment dysregulation, biological phenotype, and potential therapeutic approaches. Proteogenomic analyses revealed that the EMT, TGF-β and angiogenesis pathways were enriched in the KM2 subtype and that the KM2 subtype was associated with the mesenchymal phenotype-related CMS4 subtype, which indicated stromal invasion and worse prognosis. The KM1 subtype was characterized predominantly by activation of the cell cycle, E2F and RNA transcription and was associated with the chromosomal instability (CIN)-related ProS-E proteomic subtype, which suggested cyclin-dependent features and better survival outcomes. Moreover, drug sensitivity analyses based on three compound databases revealed subgroup-specific agents for KM1 and KM2 tumors. Conclusions: This study clarifies the molecular heterogeneity of KRAS-mutant CRC and reveals new biological subtypes and therapeutic possibilities for these tumors.

Comprehensive Analysis of a Cancer-Immunity Cycle-Based Signature for Predicting Prognosis and Immunotherapy Response in Patients With Colorectal Cancer

Immune checkpoint blockade (ICB) has been recognized as a promising immunotherapy for colorectal cancer (CRC); however, most patients have little or no clinical benefit. This study aimed to develop a novel cancer-immunity cycle–based signature to stratify prognosis of patients with CRC and predict efficacy of immunotherapy. CRC samples from The Cancer Genome Atlas (TCGA) were used as the training set, while the RNA data from Gene Expression Omnibus (GEO) data sets and real-time quantitative PCR (RT-qPCR) data from paired frozen tissues were used for validation. We built a least absolute shrinkage and selection operator (LASSO)-Cox regression model of the cancer-immunity cycle–related gene signature in CRC. Patients who scored low on the risk scale had a better prognosis than those who scored high. Notably, the signature was an independent prognostic factor in multivariate analyses, and to improve prognostic classification and forecast accuracy for individual patients, a scoring nomogram was created. The comprehensive results revealed that the low-risk patients exhibited a higher degree of immune infiltration, a higher immunoreactivity phenotype, stronger expression of immune checkpoint–associated genes, and a superior response to ICB therapy. Furthermore, the risk model was closely related to the response to multiple chemotherapeutic drugs. Overall, we developed a reliable cancer-immunity cycle–based risk model to predict the prognosis, the molecular and immune status, and the immune benefit from ICB therapy, which may contribute greatly to accurate stratification and precise immunotherapy for patients with CRC.

KIFC3 Promotes Proliferation, Migration, and Invasion in Colorectal Cancer via PI3K/AKT/mTOR Signaling Pathway

Background: KIFC3, belongs to kinesin superfamily proteins (KIFs), is well known for its role in intracellular cargo movement. KIFC3 has been identified as a docetaxel resistance gene in breast cancer cells, however, the role of KIFC3 and its potential mechanism in colorectal cancer (CRC) remains elusive.

Objectives: We aims to investigate the effects of KIFC3 in proliferation, migration, and invasion in CRC as well as the potential mechanism inside.

Methods: We investigated the expression of KIFC3 in the Oncomine, Gene Expression Profiling Interactive Analysis databases. The KIFC3 protein expression and mRNA level in CRC cells were evaluated by western blot and qRT-PCR. Cell proliferation ability was detected by CCK-8, EdU, colony formation assay and xenograft tumor in nude mice. Flow cytometry was used to detect the cell cycle. The effect of KIFC3 on the epithelial-to-mesenchymal transition (EMT) was investigated by transwell and wound healing assay. The association of KIFC3 with EMT and PI3K/AKT/mTOR signaling pathway were measured by western blot and immunofluorescence staining.

Results: The expression of KIFC3 was higher in CRC tissues than normal colorectal tissue, and was negatively correlated with the overall survival of patients with CRC. KIFC3 silencing inhibited the proliferation, migration and invasion of CRC cells. Meanwhile, it could decrease the number of cells in S phase. KIFC3 silencing inhibited the expression of proliferating cell nuclear antigen, Cyclin A2, Cyclin E1, and CDK2 and increased the expression of p21 and p53. KIFC3 overexpression promoted the G1/S phase transition. KIFC3 silencing inhibited the EMT process, which decreased the level of N-cadherin, Vimentin, SNAIL 1, TWIST, MMP-2, MMP-9 and increased E-cadherin, while KIFC3 overexpression show the opposite results. Furthermore, the knockdown of KIFC3 suppressed the EMT process by modulating the PI3K/AKT/mTOR signaling pathway. KIFC3 silencing decreased the expression of phosphorylated PI3K, AKT, mTOR, but total PI3K, AKT, mTOR have no change. Inversely, the upregulation of KIFC3 increased the expression of phosphorylated PI3K, AKT and mTOR, total PI3K, AKT, mTOR have no change. In a xenograft mouse model, the depletion of KIFC3 suppressed tumor growth. the increased expression levels of KIFC3 could enhance the proliferation, migration and invasion of CRC cells, and enhance the EMT process through the PI3K/AKT/mTOR pathway.

Conclusion: Our study substantiates that KIFC3 can participate in the regulation of CRC progression by which regulates EMT via the PI3K/AKT/mTOR axis.

Exploring immune-related signatures for predicting immunotherapeutic responsiveness, prognosis, and diagnosis of patients with colon cancer

The present study focused on identifying the immune-related signatures and exploring their performance in predicting the prognosis, immunotherapeutic responsiveness, and diagnosis of patients with colon cancer. Firstly, the immunotherapeutic response-related differential expressed genes (DEGs) were identified by comparing responders and non-responders from an anti-PD-L1 cohort using the edgeR R package. Then, the immunotherapeutic response related DEGs was intersected with immune-related genes (IRGs) to obtain the immunotherapeutic response and immune-related genes (IRIGs). Then, an immunotherapeutic response and immune-related risk score (IRIRScore) model consisting of 6 IRIGs was constructed using the univariable Cox regression analysis and multivariate Cox regression analysis based on the COAD cohort from the cancer genome atlas (TCGA) database, which was further validated in two independent gene expression omnibus database (GEO) datasets (GSE39582 and GSE17536) and anti-PD-L1 cohort. A nomogram with good accuracy was established based on the immune-related signatures and clinical factors (C-index = 0.75). In the training dataset and GSE39582, higher IRIRScore was significantly associated with higher TMN and advanced pathological stages. Based on the anti-PD-L1 cohort, patients who were sensitive to immunotherapy had significantly lower risk score than non-responders. Furthermore, we explored the immunotherapy-related signatures based on the training dataset. Kaplan-Meier curve revealed a high level of T cells regulatory (Tregs) was significantly related to poor overall survival (OS), while a high level of T cells CD4 memory resting was significantly related to better OS. Besides, the TMB value of patients in the high-risk group was significantly higher than those in a low-risk group. Moreover, patients in the high-risk group had significantly higher expression levels of immune checkpoint inhibitors. In addition, the immune-related signatures were applied to establish prediction models using the random forest algorithm. Among them, TDGF1 and NRG1 revealed excellent diagnostic predictive performance (AUC >0.8). In conclusion, the current findings provide new insights into immune-related immunotherapeutic responsiveness, prognosis, and diagnosis of colon cancer.

Modulation of Lymphocyte Functions in the Microenvironment by Tumor Oncogenic Pathways

Despite the broad application of different immunotherapeutic strategies for the treatment of solid as well as hematopoietic cancers, the efficacy of these therapies is still limited, with only a minority of patients having a long-term benefit resulting in an improved survival rate. In order to increase the response rates of patients to the currently available immunotherapies, a better understanding of the molecular mechanisms underlying the intrinsic and/or extrinsic resistance to treatment is required. There exist increasing evidences that activation of different oncogenic pathways as well as inactivation of tumor suppressor genes (TSG) in tumor cells inhibit the immune cell recognition and influegnce the composition of the tumor microenvironment (TME), thus leading to an impaired anti-tumoral immune response. A deeper understanding of the link between the tumor milieu and genomic alterations of TSGs and oncogenes is indispensable for the optimization of immunotherapies and to predict the patients’ response to these treatments. This review summarizes the role of different cancer-related, oncogene- and TSG-controlled pathways in the context of anti-tumoral immunity and response to different immunotherapies.

Deciphering the tumor cell-infiltrating landscapes reveal microenvironment subtypes and therapeutic potentials for nonsquamous NSCLC

Recent studies highlighted the clinicopathologic importance of tumor microenvironment (TME) in delineating molecular attributes and therapeutic potentials. However, the overall TME cell-infiltration landscape in non-squamous NSCLC have not been comprehensively recognized. In this study, we employed consensus non-negative matrix factorization (NMF) molecular subtyping to determine the TME cell infiltration patterns and identified three TME clusters (TME-C1, -C2, -C3) characterized by distinct clinicopathologic features, infiltrating cells, and biological processes. Proteomics analyses revealed that cGAS-STING immune signaling mediated protein and phosphorylation level were significantly upregulated in inflamed-related TME-C2 clusters. The TMEsig-score extracted from the TME-related signature divided NSCLC patients into high- and low-score subgroups, where a high score was associated with favorable prognosis and immune infiltration. Genomic landscape revealed that patients with low TMEsig-score harbored greater somatic copy number alternations and higher mutation frequency of driver genes involving STK11, KEAP1 and SMARCA4 et al. Drug sensitivity analyses suggested that tumors with high TMEsig-score were responsible for favorable clinical response to immune check-point inhibitors (ICI) treatment. In summary, this study highlights that comprehensive recognizing of the TME cell infiltration landscape will contribute to enhance our understanding of TME immune regulation and promote effectiveness of precision biotherapy strategies.

Comprehensive Analysis of Microsatellite-Related Transcriptomic Signature and Identify Its Clinical Value in Colon Cancer

Background

Microsatellite has been proved to be an important prognostic factor and a treatment reference in colon cancer. The transcriptome profile and tumor microenvironment of different microsatellite statuses are different. Metastatic colon cancer patients with microsatellite instability-high (MSI-H) are sensitive to immune checkpoint inhibitors (ICIs), but not fluorouracil. Efforts have been devoted to identify the predictive factors of immunotherapy.

Methods

We analyzed the transcriptome profile of different microsatellite statuses in colon cancer by using single-cell and bulk transcriptome data from publicly available databases. The immune cells in the tumor microenvironment were analyzed by the ESTIMATION algorithm. The microsatellite-related gene signature (MSRS) was constructed by the least absolute shrinkage and selection operator (LASSO) Cox regression based on the differentially expressed genes (DEGs) and its prognostic value and predictive value of response to immunotherapy were assessed. The prognostic value of the MSRS was also validated in another cohort.

Results

The MSI-H cancers cells were clustered differentially in the dimension reduction plot. Most of the immune cells have a higher proportion in the tumor immune microenvironment, except for CD56 bright natural killer cells. A total of 238 DEGs were identified. Based on the 238 DEGs, a neural network was constructed with a Kappa coefficient of 0.706 in the testing cohort. The MSRS is a favorable prognostic factor of overall survival, which was also validated in another cohort (GSE39582). Besides, MSRS is correlated with tumor mutation burden in MSI-H colon cancer. However, the MSRS is a barely satisfactory factor in predicting immunotherapy with the area under the curve (AUC) of 0.624.

Conclusion

We developed the MSRS, which is a robust prognostic factor of overall survival in spite of a barely satisfactory immunotherapy predictor. Further studies may need to improve the predictive ability.

Exploring Immune-Related Prognostic Signatures in the Tumor Microenvironment of Colon Cancer

Background: Colon cancer is a common malignant tumor with poor prognosis. The aim of this study is to explore the immune-related prognostic signatures and the tumor immune microenvironment of colon cancer.

Methods: The mRNA expression data of TCGA-COAD from the UCSC Xena platform and the list of immune-related genes (IRGs) from the ImmPort database were used to identify immune-related differentially expressed genes (DEGs). Then, we constructed an immune-related risk score prognostic model and validated its predictive performance in the test dataset, the whole dataset, and two independent GEO datasets. In addition, we explored the differences in tumor-infiltrating immune cell types, tumor mutation burden (TMB), microsatellite status, and expression levels of immune checkpoints and their ligands between the high-risk and low-risk score groups. Moreover, the potential value of the identified immune-related signature with respect to immunotherapy was investigated based on an immunotherapeutic cohort (Imvigor210) treated with an anti-PD-L1 agent.

Results: Seven immune-related DEGs were identified as prognostic signatures. The areas under the curves (AUCs) of the constructed risk score model for overall survival (OS) were calculated (training dataset: 0.780 at 3 years, 0.801 at 4 years, and 0.766 at 5 years; test dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years; and the whole dataset: 0.642 at 3 years, 0.647 at 4 years, and 0.629 at 5 years). In the high-risk score group of the whole dataset, patients had worse OS, higher TMN stages, advanced pathological stages, and a higher TP53 mutation rate (p < 0.05). In addition, a high level of resting NK cells or M0 macrophages, and high TMB were significantly related to poor OS (p < 0.05). Also, we observed that high-risk score patients had a high expression level of PD-L1, PD-1, and CTLA-4 (p < 0.05). The patients with high-risk scores demonstrated worse prognosis than those with low-risk scores in multiple datasets (GSE39582: p = 0.0023; GSE17536: p = 0.0008; immunotherapeutic cohort without platinum treatment: p = 0.0014; immunotherapeutic cohort with platinum treatment: p = 0.0027).

Conclusion: We developed a robust immune-related prognostic signature that performed great in multiple cohorts and explored the characteristics of the tumor immune microenvironment of colon cancer patients, which may give suggestions for the prognosis and immunotherapy in the future.

Identifying changes in immune cells and constructing prognostic models using immune-related genes in post-burn immunosuppression

BACKGROUND

Burn patients are prone to infection as well as immunosuppression, which is a significant cause of death. Currently, there is a lack of prognostic biomarkers for immunosuppression in burn patients. This study was conducted to identify immune-related genes that are prognosis biomarkers in post-burn immunosuppression and potential targets for immunotherapy.

METHODS

We downloaded the gene expression profiles and clinical data of 213 burn patients and 79 healthy samples from the Gene Expression Omnibus (GEO) database. Immune infiltration analysis was used to identify the proportion of circulating immune cells. Functional enrichment analyses were carried out to identify immune-related genes that were used to build miRNA-mRNA networks to screen key genes. Next, we carried out correlation analysis between immune cells and key genes that were then used to construct logistic regression models in GSE77791 and were validated in GSE19743. Finally, we determined the expression of key genes in burn patients using quantitative reverse transcription polymerase chain reaction (qRT-PCR).

RESULTS

A total of 745 differently expressed genes were screened out: 299 were up-regulated and 446 were down-regulated. The number of Th-cells (CD4+) decreased while neutrophils increased in burn patients. The enrichment analysis showed that down-regulated genes were enriched in the T-cell activation pathway, while up-regulated genes were enriched in neutrophil activation response in burn patients. We screened out key genes (NFATC2, RORA, and CAMK4) that could be regulated by miRNA. The expression of key genes was related to the proportion of Th-cells (CD4+) and survival, and was an excellent predictor of prognosis in burns with an area under the curve (AUC) value of 0.945. Finally, we determined that NFATC2, RORA, and CAMK4 were down-regulated in burn patients.

CONCLUSION

We found that NFATC2, RORA, and CAMK4 were likely prognostic biomarkers in post-burn immunosuppression and potential immunotherapeutic targets to convert Th-cell dysfunction.

Characterization of Two Ferroptosis Subtypes With Distinct Immune Infiltration and Gender Difference in Gastric Cancer

Background: Iron is an essential nutrient involved in the redox cycle and the formation of free radicals. The reprogramming of iron metabolism is the main link to tumor cell survival. Ferroptosis is an iron-dependent form of regulated cell death associated with cancer; the characteristics of ferroptosis in cancers are still uncertain. This study aimed to explore the application value and gender difference of ferroptosis in prognosis and immune prediction to provide clues for targeted therapy of gastric cancer.

Methods: We comprehensively evaluated the ferroptosis levels of 1,404 gastric cancer samples from six independent GC cohorts based on ferroptosis-related specific genes and systematically correlated ferroptosis with immune cell infiltrating and gender characteristics. The ferroptosis score was constructed to quantify the ferroptosis levels of individual tumors using principal component analysis (PCA) algorithms.

Results: We identified two distinct ferroptosis subtypes in gastric cancer, namely Subtype-A and Subtype-B. We found that male patients in Subtype-B had the worst prognosis in contrast with the other groups. Three sex hormone receptors (AR, ER, and PR) in Subtype-B tumor patients were higher than in Subtype-A tumor patients in GC, while the HER2 displayed an opposite trend. We developed a risk model termed ferroptosis score to evaluate ferroptosis levels within individual tumors. The low-ferroptosis score group was characterized by activation of immune cells and increased mutation burden, which is also linked to increased neoantigen load and enhanced response to anti-PD-1/L1 immunotherapy. The patients with a low-ferroptosis score showed a high microsatellite instability status (MSI-H) and had a higher response to immunotherapy. Furthermore, the patients with low-ferroptosis scores have a lower estimated IC50 in the several chemotherapy drugs, including paclitaxel, gemcitabine, and methotrexate.

Conclusions: We revealed that sex hormone receptors and immune cell infiltration were markedly different between ferroptosis subtypes in GC patients. The results suggested that gender difference may be critical when the ferroptosis-related strategy is applied in GC treatment. Further, ferroptosis levels were identified with an extreme variety of prognosis and tumor immune characteristics, which might benefit GC individualized treatment.

Identification of m6A Regulator-Associated Methylation Modification Clusters and Immune Profiles in Melanoma

RNA N6-methyladenosine (m⁶A) modification in tumorigenesis and progression has been highlighted and discovered in recent years. However, the molecular and clinical implications of m⁶A modification in melanoma tumor microenvironment (TME) and immune infiltration remain largely unknown. Here, we utilized consensus molecular clustering with nonnegative matrix factorization based on the melanoma transcriptomic profiles of 23 m⁶A regulators to determine the m⁶A modification clusters and m⁶A-related gene signature. Three distinct m⁶A modification patterns (m⁶A-C1, C2, and C3), which are characterized by specific m⁶A regulator expression, survival outcomes, and biological pathways, were identified in more than 1,000 melanoma samples. The immune profile analyses showed that these three m⁶A modification subtypes were highly consistent with the three known immune phenotypes: immune-desert (C1), immune-excluded (C2), and immune-inflamed (C3). Tumor digital cytometry (CIBERSORT, ssGSEA) algorithm revealed an upregulated infiltration of CD8⁺ T cell and NK cell in m⁶A-C3 subtype. An m⁶A scoring scheme calculated by principal component of m⁶A signatures stratified melanoma patients into high- and low-m⁶sig score subgroups; a high score was significantly associated with prolonged survival and enhanced immune infiltration. Furthermore, fewer somatic copy number alternations (SCNA) and PD-L1 expression were found in patients with high m⁶Sig score. In addition, patients with high m⁶Sig score demonstrated marked immune responses and durable clinical benefits in two independent immunotherapy cohorts. Overall, this study indicated that m⁶A modification is involved in melanoma tumor microenvironment immune regulation and contributes to formation of tumor immunogenicity. Comprehensive evaluation of the m⁶A modification pattern of individual tumors will provide more insights into molecular mechanisms of TME characterization and promote more effective personalized biotherapy strategies.

Identification of a novel immune signature for optimizing prognosis and treatment prediction in colorectal cancer

BACKGROUND

Globally, colorectal cancer (CRC) is one of the most lethal malignant diseases. However, the currently approved therapeutic options for CRC failed to acquire satisfactory treatment efficacy. Tailoring therapeutic strategies for CRC individuals can provide new insights into personalized prediction approaches and thus maximize clinical benefits.

METHODS

In this study, a multi-step process was used to construct an immune-related genes (IRGs) based signature leveraging the expression profiles and clinical characteristics of CRC from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. An integrated immunogenomic analysis was performed to determine the association between IRGs with prognostic significance and cancer genotypes in the tumor immune microenvironment (TIME). Moreover, we performed a comprehensive in silico therapeutics screening to identify agents with subclass-specific efficacy.

RESULTS

The established signature was shown to be a promising biomarker for evaluating clinical outcomes in CRC. The immune risk score as calculated by this classifier was significantly correlated with over-riding malignant phenotypes and immunophenotypes. Further analyses demonstrated that CRCs with low immune risk scores achieved better therapeutic benefits from immunotherapy, while AZD4547, Cytochalasin B and S-crizotinib might have potential therapeutic implications in the immune risk score-high CRCs.

CONCLUSIONS

Overall, this IRGs-based signature not only afforded a useful tool for determining the prognosis and evaluating the TIME features of CRCs, but also shed new light on tailoring CRCs with precise treatment.

DNM1: A Prognostic Biomarker Associated with Immune Infiltration in Colon Cancer-A Study Based on TCGA Database

Aim

The aim of our work was to determine the utility of DNM1 as a biomarker for the diagnosis and prognosis of colon cancer (CC).

Methods

DNM1 expression variations in CC vs. normal tissues were investigated using The Cancer Genome Atlas (TCGA) database. The association of DNM1 expression levels with the clinicopathological variables in CC prognosis was investigated using logistic regression analyses. Independent prognostic factors for CC were evaluated using univariate and multivariate Cox regression analyses. The correlation between DNM1 expression and immune cell infiltration was estimated using single-sample Gene Set Enrichment Analysis (ssGSEA).

Results

DNM1 expression in CC tissues was significantly higher than that in normal tissues. High DNM1 expression was significantly correlated with M stage, N stage, perineural invasion and lymphatic invasion and predicted poor prognosis. The univariate analysis highlighted that DNM1 was an independent CC risk factor. Results of ssGSEA showed that DNM1 was linked to several cancer-related pathways, including the neuroactive ligand-receptor interaction, hypertrophic cardiomyopathy, ECM-receptor interaction, dilated cardiomyopathy, and calcium signaling pathway. Moreover, DNM1 expression was positively correlated with the level of infiltration by Neutrophils, Tregs, NK cells, and Macrophages.

Conclusion

DNM1 has a significant function and has diagnostic and prognostic potential for CC.