GB1275, a first-in-class CD11b modulator: rationale for immunotherapeutic combinations in solid tumors

Dual depletion of myeloid-derived suppressor cells and tumor cells with self-assembled gemcitabine-celecoxib nano-twin drug for cancer chemoimmunotherapy

Myeloid-derived suppressor cells (MDSCs) have played a significant role in facilitating tumor immune escape and inducing an immunosuppressive tumor microenvironment. Eliminating MDSCs and tumor cells remains a major challenge in cancer immunotherapy. A novel approach has been developed using gemcitabine-celecoxib twin drug-based nano-assembled carrier-free nanoparticles (GEM-CXB NPs) for dual depletion of MDSCs and tumor cells in breast cancer chemoimmunotherapy. The GEM-CXB NPs exhibit prolonged blood circulation, leading to the preferential accumulation and co-release of GEM and CXB in tumors. This promotes synergistic chemotherapeutic activity by the proliferation inhibition and apoptosis induction against 4T1 tumor cells. In addition, it enhances tumor immunogenicity by immunogenic cell death induction and MDSC-induced immunosuppression alleviation through the depletion of MDSCs. These mechanisms synergistically activate the antitumor immune function of cytotoxic T cells and natural killer cells, inhibit the proliferation of regulatory T cells, and promote the M2 to M1 phenotype repolarization of tumor-associated macrophages, considerably enhancing the overall antitumor and anti-metastasis efficacy in BALB/c mice bearing 4T1 tumors. The simplified engineering of GEM-CXB NPs, with their dual depletion strategy targeting immunosuppressive cells and tumor cells, represents an advanced concept in cancer chemoimmunotherapy.

Current and future immunotherapeutic approaches in pancreatic cancer treatment

Pancreatic cancer is a major cause of cancer-related death, but despondently, the outlook and prognosis for this resistant type of tumor have remained grim for a long time. Currently, it is extremely challenging to prevent or detect it early enough for effective treatment because patients rarely exhibit symptoms and there are no reliable indicators for detection. Most patients have advanced or spreading cancer that is difficult to treat, and treatments like chemotherapy and radiotherapy can only slightly prolong their life by a few months. Immunotherapy has revolutionized the treatment of pancreatic cancer, yet its effectiveness is limited by the tumor's immunosuppressive and hard-to-reach microenvironment. First, this article explains the immunosuppressive microenvironment of pancreatic cancer and highlights a wide range of immunotherapy options, including therapies involving oncolytic viruses, modified T cells (T-cell receptor [TCR]-engineered and chimeric antigen receptor [CAR] T-cell therapy), CAR natural killer cell therapy, cytokine-induced killer cells, immune checkpoint inhibitors, immunomodulators, cancer vaccines, and strategies targeting myeloid cells in the context of contemporary knowledge and future trends. Lastly, it discusses the main challenges ahead of pancreatic cancer immunotherapy.

Cellular collusion: cracking the code of immunosuppression and chemo resistance in PDAC

Despite the efforts, pancreatic ductal adenocarcinoma (PDAC) is still highly lethal. Therapeutic challenges reside in late diagnosis and establishment of peculiar tumor microenvironment (TME) supporting tumor outgrowth. This stromal landscape is highly heterogeneous between patients and even in the same patient. The organization of functional sub-TME with different cellular compositions provides evolutive advantages and sustains therapeutic resistance. Tumor progressively establishes a TME that can suit its own needs, including proliferation, stemness and invasion. Cancer-associated fibroblasts and immune cells, the main non-neoplastic cellular TME components, follow soluble factors-mediated neoplastic instructions and synergize to promote chemoresistance and immune surveillance destruction. Unveiling heterotypic stromal-neoplastic interactions is thus pivotal to breaking this synergism and promoting the reprogramming of the TME toward an anti-tumor milieu, improving thus the efficacy of conventional and immune-based therapies. We underscore recent advances in the characterization of immune and fibroblast stromal components supporting or dampening pancreatic cancer progression, as well as novel multi-omic technologies improving the current knowledge of PDAC biology. Finally, we put into context how the clinic will translate the acquired knowledge to design new-generation clinical trials with the final aim of improving the outcome of PDAC patients.

Study on the mechanism of MDSC-platelets and their role in the breast cancer microenvironment

Myeloid-derived suppressor cells (MDSCs) are key immunosuppressive cells in the tumor microenvironment (TME) that play critical roles in promoting tumor growth and metastasis. Tumor-associated platelets (TAPs) help cancer cells evade the immune system and promote metastasis. In this paper, we describe the interaction between MDSCs and TAPs, including their generation, secretion, activation, and recruitment, as well as the effects of MDSCs and platelets on the generation and changes in the immune, metabolic, and angiogenic breast cancer (BC) microenvironments. In addition, we summarize preclinical and clinical studies, traditional Chinese medicine (TCM) therapeutic approaches, and new technologies related to targeting and preventing MDSCs from interacting with TAPs to modulate the BC TME, discuss the potential mechanisms, and provide perspectives for future development. The therapeutic strategies discussed in this review may have implications in promoting the normalization of the BC TME, reducing primary tumor growth and distant lung metastasis, and improving the efficiency of anti-tumor therapy, thereby improving the overall survival (OS) and progression-free survival (PFS) of patients. However, despite the significant advances in understanding these mechanisms and therapeutic strategies, the complexity and heterogeneity of MDSCs and side effects of antiplatelet agents remain challenging. This requires further investigation in future prospective cohort studies.

Integrins in Health and Disease-Suitable Targets for Treatment?

Integrin receptors are heterodimeric surface receptors that play multiple roles regarding cell-cell communication, signaling, and migration. The four members of the β2 integrin subfamily are composed of an alternative α (CD11a-d) subunit, which determines the specific receptor properties, and a constant β (CD18) subunit. This review aims to present insight into the multiple immunological roles of integrin receptors, with a focus on β2 integrins that are specifically expressed by leukocytes. The pathophysiological role of β2 integrins is confirmed by the drastic phenotype of patients suffering from leukocyte adhesion deficiencies, most often resulting in severe recurrent infections and, at the same time, a predisposition for autoimmune diseases. So far, studies on the role of β2 integrins in vivo employed mice with a constitutive knockout of all β2 integrins or either family member, respectively, which complicated the differentiation between the direct and indirect effects of β2 integrin deficiency for distinct cell types. The recent generation and characterization of transgenic mice with a cell-type-specific knockdown of β2 integrins by our group has enabled the dissection of cell-specific roles of β2 integrins. Further, integrin receptors have been recognized as target receptors for the treatment of inflammatory diseases as well as tumor therapy. However, whereas both agonistic and antagonistic agents yielded beneficial effects in animal models, the success of clinical trials was limited in most cases and was associated with unwanted side effects. This unfavorable outcome is most probably related to the systemic effects of the used compounds on all leukocytes, thereby emphasizing the need to develop formulations that target distinct types of leukocytes to modulate β2 integrin activity for therapeutic applications.

Research trends on immunotherapy for pancreatic cancer: A bibliometric analysis

This study aims to summarize and visually analyze the current research status in pancreatic cancer immunotherapy during the past two decades by bibliometrics and explore the current research hotspots and future development directions. The literature related to pancreatic cancer immunotherapy from 2002 to 2021 was downloaded from the core database of the Web of Science. VOSviewer and CiteSpace software were used to visualize the included literature. A total of 2528 articles were included. In the past two decades, publications in the pancreatic cancer immunotherapy field have increased almost annually. As the country with the largest publications, the United States has various research institutions dedicated to pancreatic cancer immunotherapy. Jaffee EM and Zheng L from Johns Hopkins University and Vonderheide RH from the University of Pennsylvania have published the most articles in this field. The current research hotspots of pancreatic cancer immunotherapy include the tumor microenvironment, immune cells, immune checkpoint blockade, and combination therapy. The study of novel immunotherapies and combination therapy may become the primary focus of future research on pancreatic cancer immunotherapy. More prospective clinical studies with high evidence levels should be conducted.

Hydrogel-Based Therapeutics for Pancreatic Ductal Adenocarcinoma Treatment

Pancreatic ductal adenocarcinoma (PDAC), one of the deadliest malignancies worldwide, is characteristic of the tumor microenvironments (TME) comprising numerous fibroblasts and immunosuppressive cells. Conventional therapies for PDAC are often restricted by limited drug delivery efficiency, immunosuppressive TME, and adverse effects. Thus, effective and safe therapeutics are urgently required for PDAC treatment. In recent years, hydrogels, with their excellent biocompatibility, high drug load capacity, and sustainable release profiles, have been developed as effective drug-delivery systems, offering potential therapeutic options for PDAC. This review summarizes the distinctive features of the immunosuppressive TME of PDAC and discusses the application of hydrogel-based therapies in PDAC, with a focus on how these hydrogels remodel the TME and deliver different types of cargoes in a controlled manner. Furthermore, we also discuss potential drug candidates and the challenges and prospects for hydrogel-based therapeutics for PDAC. By providing a comprehensive overview of hydrogel-based therapeutics for PDAC treatment, this review seeks to serve as a reference for researchers and clinicians involved in developing therapeutic strategies targeting the PDAC microenvironment.

Comprehensive analysis of clinical prognostic features and tumor microenvironment landscape of CD11b+CD64+ patients with acute myeloid leukemia

BACKGROUND

Immunophenotyping surface molecules detected in the clinic are mainly applied in diagnostic confirmation and subtyping. However, the immunomodulatory molecules CD11b and CD64, are highly associated with leukemogenesis. Hence, the prognostic value of them and their potential biological functions merit further investigation.

METHODS

Flow cytometry was operated to detect immunophenotypic molecules from AML bone marrow samples. Multivariate cox regression, Kaplan-Meier analyses, and nomogram were conducted to predict survival. Transcriptomic data, lymphocyte subsets, and immunohistochemical staining were incorporated to identify potential biological functions of prognostic immunophenotype in acute myeloid leukemia (AML).

RESULTS

We classified 315 newly diagnosed AML patients of our center based on the expression of CD11b and CD64. The CD11b+CD64+ populations were identified as independent risk factors for overall survival and event-free survival of AML, exhibiting specific clinicopathological features. The predictive models based on CD11b+CD64+ showed high classification performance. In addition, the CD11b+CD64+ subset, characterized by high inhibitory immune checkpoints, M2-macrophage infiltration, low anti-tumor effector cells infiltration, as well as abnormal somatic mutation landscape, presented a distinctive tumor microenvironmental landscape. The CD11b+CD64+ population showd a higher expression of BCL2, and the drug sensitivity indicated that they presented a lower half-maximal inhibitory concentration value for BCL2 inhibitor, and could benefit more from the above medicine.

CONCLUSIONS

This work might be of benefit to enhanced understanding of CD11b+CD64+ in the prognosis and leukemogenesis, and yielded novel biomarkers to guide immunotherapy and targeted therapy for AML.

Carbohydrate ligand engagement with CD11b enhances differentiation of tumor-associated myeloid cells for immunotherapy of solid cancers

BACKGROUND

Efforts to modulate the function of tumor-associated myeloid cell are underway to overcome the challenges in immunotherapy and find a cure. One potential therapeutic target is integrin CD11b, which can be used to modulate the myeloid-derived cells and induce tumor-reactive T-cell responses. However, CD11b can bind to multiple different ligands, leading to various myeloid cell functions such as adhesion, migration, phagocytosis, and proliferation. This has created a major challenge in understanding how CD11b converts the differences in the receptor-ligand binding into subsequent signaling responses and using this information for therapeutic development.

METHODS

This study aimed to investigate the antitumor effect of a carbohydrate ligand, named BG34-200, which modulates the CD11b⁺ cells. We have applied peptide microarrays, multiparameter FACS (fluorescence-activated cell analysis) analysis, cellular/molecular immunological technology, advanced microscopic imaging, and transgenic mouse models of solid cancers, to study the interaction between BG34-200 carbohydrate ligand and CD11b protein and the resulting immunological changes in the context of solid cancers, including osteosarcoma, advanced melanoma, and pancreatic ductal adenocarcinoma (PDAC).

RESULTS

Our results show that BG34-200 can bind directly to the activated CD11b on its I (or A) domain, at previously unreported peptide residues, in a multisite and multivalent manner. This engagement significantly impacts the biological function of tumor-associated inflammatory monocytes (TAIMs) in osteosarcoma, advanced melanoma, and PDAC backgrounds. Importantly, we observed that the BG34-200-CD11b engagement triggered endocytosis of the binding complexes in TAIMs, which induced intracellular F-actin cytoskeletal rearrangement, effective phagocytosis, and intrinsic ICAM-1 (intercellular adhesion molecule I) clustering. These structural biological changes resulted in the differentiation in TAIMs into monocyte-derived dendritic cells, which play a crucial role in T-cell activation in the tumor microenvironment.

CONCLUSIONS

Our research has advanced the current understanding of the molecular basis of CD11b activation in solid cancers, revealing how it converts the differences in BG34 carbohydrate ligands into immune signaling responses. These findings could pave the way for the development of safe and novel BG34-200-based therapies that modulate myeloid-derived cell functions, thereby enhancing immunotherapy for solid cancers.

A novel signature predicts prognosis and immunotherapy in lung adenocarcinoma based on cancer-associated fibroblasts

Background

Extensive research has established the significant correlations between cancer-associated fibroblasts (CAFs) and various stages of cancer development, including initiation, angiogenesis, progression, and resistance to therapy. In this study, we aimed to investigate the characteristics of CAFs in lung adenocarcinoma (LUAD) and develop a risk signature to predict the prognosis of patients with LUAD.

Methods

We obtained single-cell RNA sequencing (scRNA-seq) and bulk RNA-seq data from the public database. The Seurat R package was used to process the scRNA-seq data and identify CAF clusters based on several biomarkers. CAF-related prognostic genes were further identified using univariate Cox regression analysis. To reduce the number of genes, Lasso regression was performed, and a risk signature was established. A novel nomogram that incorporated the risk signature and clinicopathological features was developed to predict the clinical applicability of the model. Additionally, we conducted immune landscape and immunotherapy responsiveness analyses. Finally, we performed in vitro experiments to verify the functions of EXO1 in LUAD.

Results

We identified 5 CAF clusters in LUAD using scRNA-seq data, of which 3 clusters were significantly associated with prognosis in LUAD. A total of 492 genes were found to be significantly linked to CAF clusters from 1731 DEGs and were used to construct a risk signature. Moreover, our immune landscape exploration revealed that the risk signature was significantly related to immune scores, and its ability to predict responsiveness to immunotherapy was confirmed. Furthermore, a novel nomogram incorporating the risk signature and clinicopathological features showed excellent clinical applicability. Finally, we verified the functions of EXP1 in LUAD through in vitro experiments.

Conclusions

The risk signature has proven to be an excellent predictor of LUAD prognosis, stratifying patients more appropriately and precisely predicting immunotherapy responsiveness. The comprehensive characterization of LUAD based on the CAF signature can predict the response of LUAD to immunotherapy, thus offering fresh perspectives into the management of LUAD patients. Our study ultimately confirms the role of EXP1 in facilitating the invasion and growth of tumor cells in LUAD. Nevertheless, further validation can be achieved by conducting in vivo experiments.

Pancreatic cancer: Advances and challenges

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers. Significant efforts have largely defined major genetic factors driving PDAC pathogenesis and progression. Pancreatic tumors are characterized by a complex microenvironment that orchestrates metabolic alterations and supports a milieu of interactions among various cell types within this niche. In this review, we highlight the foundational studies that have driven our understanding of these processes. We further discuss the recent technological advances that continue to expand our understanding of PDAC complexity. We posit that the clinical translation of these research endeavors will enhance the currently dismal survival rate of this recalcitrant disease.

Leukadherin-1 inhibits NLRP3 inflammasome by blocking inflammasome assembly

Aberrant activation of the NLRP3 inflammasome has been implicated in the occurrence and development of many inflammatory diseases, and thus potent inhibitors of the NLRP3 inflammasome should be explored. An antitumor agent, Leukadherin-1 (LA-1), tested in phase 1/2 clinical trials, has been reported to exert anti-inflammatory properties by blocking the NF-κB pathway. However, the effects of LA-1 on the NLRP3 inflammasome have not been conclusively determined. In this study, we found that at lower doses (below 1 μM) ex vivo, LA-1 blocked NLRP3 inflammasome activation without affecting NF-κB signaling. Accordingly, 1 mg/Kg LA-1 strongly inhibited the release of NLRP3-dependent cytokine, but only slightly inhibited NLRP3-independent-cytokines secretion in endotoxemia and alleviated NLRP3-dependent peritonitis in vivo. Mechanistically, LA-1 had no effects on ion flux or mitochondrial injury. Instead, it inhibited NLRP3 inflammasome assembly by suppressing ASC oligomerization, blocking NLRP3 self-assembly, and reducing interactions of NLRP3 with ASC and NEK7. Therefore, LA-1 inhibits NLRP3 inflammasome activation, implying that it is a potential treatment option for NLRP3-associated diseases.

Clear Cell Renal Cell Carcinoma: A Comprehensive in silico Study in Searching for Therapeutic Targets

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is recognized as one of the leading causes of illness and death worldwide. Understanding the molecular mechanisms in ccRCC pathogenesis is crucial for discovering novel therapeutic targets and developing efficient drugs. With the application of a comprehensive in silico analysis of the ccRCC-related array sets, the main objective of this study was to discover the top molecules and pathways in the pathogenesis of this cancer.

METHODS

ccRCC microarray datasets were downloaded from the Gene Expression Omnibus database, and after quality checking, normalization, and analysis using the Limma algorithm, differentially expressed genes (DEGs) were identified, considering the adjusted p value <0.049. The intensity values of the identified DEGs were introduced to the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to construct co-expression modules. Functional enrichment analyses were performed using the DEGs in the disease-correlated module, and hub genes were identified among the top genes in a protein-protein interaction network and the disease most correlated module. The expression analysis of hub genes was done by utilizing GEPIA, and the GSCA server was used to compare the expression patterns of hub genes in ccRCC and other cancers. DGIdb database was utilized to identify the hub gene-related drugs.

RESULTS

Three datasets, including GSE11151, GSE12606, and GSE36897, were retrieved, merged, normalized, and analyzed. Using WGCNA, the DEGs were clustered into eight different modules. Translocation of ZAP-70 to immunological synapse, endosomal/vacuolar pathway, cell surface interactions at the vascular wall, and immune-related pathways were the topmost enriched terms for the ccRCC-correlated DEGs. Twelve genes including PTPRC, ITGAM, TLR2, CD86, PLEK, TYROBP, ITGB2, RAC2, CSF1R, CCR5, CCL5, and LCP2 were introduced as hub genes. All the 12 hub genes were upregulated in ccRCC samples and showed a positive correlation with the infiltration of different immune cells. According to the DGIdb database, 127 drugs, including tyrosine kinase inhibitors, glucocorticoids, and chemotaxis targeting molecules, were identified to interact with the hub genes.

CONCLUSION

By utilizing an integrative bioinformatics approach, this experiment shed light on the underlying pathways in the pathogenesis of ccRCC and introduced several potential therapeutic targets for repurposing or developing novel drugs for an efficient treatment of this cancer. Our next step would be to assess the gene expression profiles of the identified hubs in different cell populations in the tumor microenvironment.

Spatially restricted tumour-associated and host-associated immune drivers correlate with the recurrence sites of pancreatic cancer

OBJECTIVE

Most patients with pancreatic ductal adenocarcinoma (PDAC) will experience recurrence after resection. Here, we investigate spatially organised immune determinants of PDAC recurrence.

DESIGN

PDACs (n=284; discovery cohort) were classified according to recurrence site as liver (n=93/33%), lung (n=49/17%), local (n=31/11%), peritoneal (n=38/13%) and no-recurrence (n=73/26%). Spatial compartments were identified by fluorescent imaging as: pancytokeratin (PanCK)⁺CD45^- (tumour cells); CD45⁺PanCK^- (leucocytes) and PanCK^-CD45^- (stromal cells), followed by transcriptomic (72 genes) and proteomic analysis (51 proteins) for immune pathway targets. Results from next-generation sequencing (n=194) were integrated. Finally, 10 tumours from each group underwent immunophenotypic analysis by multiplex immunofluorescence. A validation cohort (n=109) was examined in parallel.

RESULTS

No-recurrent PDACs show high immunogenicity, adaptive immune responses and are rich in pro-inflammatory chemokines, granzyme B and alpha-smooth muscle actin⁺ fibroblasts. PDACs with liver and/or peritoneal recurrences display low immunogenicity, stemness phenotype and innate immune responses, whereas those with peritoneal metastases are additionally rich in FAP⁺ fibroblasts. PDACs with local and/or lung recurrences display interferon-gamma signalling and mixed adaptive and innate immune responses, but with different leading immune cell population. Tumours with local recurrences overexpress dendritic cell markers whereas those with lung recurrences neutrophilic markers. Except the exclusive presence of RNF43 mutations in the no-recurrence group, no genetic differences were seen. The no-recurrence group exhibited the best, whereas liver and peritoneal recurrences the poorest prognosis.

CONCLUSIONS

Our findings demonstrate distinct inflammatory/stromal responses in each recurrence group, which might affect dissemination patterns and patient outcomes. These findings may help to inform personalised adjuvant/neoadjuvant and surveillance strategies in PDAC, including immunotherapeutic modalities.

Arginase 1 is a key driver of immune suppression in pancreatic cancer

An extensive fibroinflammatory stroma rich in macrophages is a hallmark of pancreatic cancer. In this disease, it is well appreciated that macrophages are immunosuppressive and contribute to the poor response to immunotherapy; however, the mechanisms of immune suppression are complex and not fully understood. Immunosuppressive macrophages are classically defined by the expression of the enzyme Arginase 1 (ARG1), which we demonstrated is potently expressed in pancreatic tumor-associated macrophages from both human patients and mouse models. While routinely used as a polarization marker, ARG1 also catabolizes arginine, an amino acid required for T cell activation and proliferation. To investigate this metabolic function, we used a genetic and a pharmacologic approach to target Arg1 in pancreatic cancer. Genetic inactivation of Arg1 in macrophages, using a dual recombinase genetically engineered mouse model of pancreatic cancer, delayed formation of invasive disease, while increasing CD8+ T cell infiltration. Additionally, Arg1 deletion induced compensatory mechanisms, including Arg1 overexpression in epithelial cells, namely Tuft cells, and Arg2 overexpression in a subset of macrophages. To overcome these compensatory mechanisms, we used a pharmacological approach to inhibit arginase. Treatment of established tumors with the arginase inhibitor CB-1158 exhibited further increased CD8+ T cell infiltration, beyond that seen with the macrophage-specific knockout, and sensitized the tumors to anti-PD1 immune checkpoint blockade. Our data demonstrate that Arg1 drives immune suppression in pancreatic cancer by depleting arginine and inhibiting T cell activation.

Combination immunotherapy for pancreatic cancer: challenges and future considerations

INTRODUCTION

: Immune checkpoint inhibitors (ICI) have not yielded significant efficacy in pancreatic ductal adenocarcinoma (PDA), despite the role of the innate and adaptive immune systems on progression and survival. However, recently identified pathways have identified new targets and generated promising clinical investigations into promoting an effective immune-mediated antitumor response in PDA.

AREAS COVERED

: We review biological mechanisms associated with immunotherapy resistance and outline strategies for therapeutic combinations with established and novel therapies in PDA.

EXPERT OPINION

: Pancreatic cancers rarely benefits from treatment with ICI due to an immunosuppressive tumor microenvironment (TME). New understandings of factors associated with the suppressive TME, include low and poor quality neoantigens, constrained effector T cells infiltration, and the presence of a dense, suppressive myeloid cell population. These findings have been translated into new clinical investigations evaluating novel therapies in combination with ICI and/or standard systemic chemotherapy and radiotherapy. The epithelial, immune, and stromal compartments are intricately related in PDA, and the framework for successful targeting of this disease requires a comprehensive and personalized approach.

Clinical Strategies Targeting the Tumor Microenvironment of Pancreatic Ductal Adenocarcinoma

Pancreatic cancer has a complex tumor microenvironment which engages in extensive crosstalk between cancer cells, cancer-associated fibroblasts, and immune cells. Many of these interactions contribute to tumor resistance to anti-cancer therapies. Here, new therapeutic strategies designed to modulate the cancer-associated fibroblast and immune compartments of pancreatic ductal adenocarcinomas are described and clinical trials of novel therapeutics are discussed. Continued advances in our understanding of the pancreatic cancer tumor microenvironment are generating stromal and immune-modulating therapeutics that may improve patient responses to anti-tumor treatment.

Prognostic Signature, Immune Features, and Therapeutic Responses of a Novel Ubiquitination-Related Gene Signature in Lung Adenocarcinoma

Growing studies have implicated the association of ubiquitination-related genes (UbRGs) with the cancer progression and the long-term survival of patients. However, the prognostic values of UbRGs in lung adenocarcinoma (LUAD) have not been investigated. Our study aimed to establish a ubiquitination-related model for prognosis prediction and internal mechanism investigation. The transcriptome expression profiles and corresponding clinical information of LUAD were obtained from TCGA and GEO datasets. Differentially expressed genes (DEGs) were screened between LUAD specimens and nontumor specimens. Kaplan–Meier analysis and univariate assays were carried out on DEGs to preliminarily screen survival-related UbRGs. Then, the LASSO Cox regression model was applied to develop a multigene signature, which was then demonstrated in two GEO datasets by the use of Kaplan-Meier, ROC, and Cox analyses. We estimated the immune cell infiltration in tumor microenvironment via CIBERSORT and immunotherapy response through the TIDE algorithm. In this study, a total of 71 ubiquitination-related DEGs were identified. Nine UbRGs, including TUBA4A, TRIM2, PLK1, ARRB1, TRIM58, PLK1, ARRB1, CCNB1, TRIM6, PTTG1, and CCT2, were included to establish a risk model, which was validated in TCGA and GEO datasets. The multivariate assays demonstrated that the 9-UbRGs signature was a robust independent prognostic factor in the overall survival of LUAD patients. The abundance of CD8 T cells, activated CD4 T memory cells, resting NK cells and macrophages was higher in the high-risk group, and the TMB of high-risk group was statistically higher than the low-risk group. Multiple drugs approved by FAD, targeting UbRGs, were available for the treatment of LUAD. Overall, we identified a nine ubiquitination-related gene signature, and the signature may be applied to be a potential biomarker for CD8 T cells response and clinical responses to immune checkpoint inhibitors for LUAD.

Functional and Therapeutic Significance of Tumor-Associated Macrophages in Colorectal Cancer

The role of the tumor microenvironment (TME) in the progression of colorectal cancer (CRC) and its acquisition of resistance to treatment become the research hotspots. As an important component of TME, the tumor-associated macrophages (TAMs) regulate multiple critical oncogenic processes, namely, occurrence, proliferation, metastasis, and drug resistance in CRC. In this review, we have discussed the functional and therapeutic significance of TAMs in CRC. M1 macrophages act as the tumor suppressor while M2 macrophages promote CRC. The polarization of TAMs is mainly regulated by the pathways such as NFKB1 pathways, STAT3 pathways, WNT5A pathways, and PI3K pathways in CRC. Furthermore, the M2 polarization of TAMs is not only controllable but also reversible. Finally, we provide insights into the TAMs-targeted therapeutic strategies.

Identification of Immune-Cell-Related Prognostic Biomarkers of Esophageal Squamous Cell Carcinoma Based on Tumor Microenvironment

Background

Esophageal squamous cell carcinoma (ESCC) is one of the most fatal cancers in the world. The 5-year survival rate of ESCC is <30%. However, few biomarkers can accurately predict the prognosis of patients with ESCC. We aimed to identify potential survival-associated biomarkers for ESCC to improve its poor prognosis.

Methods

ImmuneAI analysis was first used to access the immune cell abundance of ESCC. Then, ESTIMATE analysis was performed to explore the tumor microenvironment (TME), and differential analysis was used for the selection of immune-related differentially expressed genes (DEGs). Weighted gene coexpression network analysis (WGCNA) was used for selecting the candidate DEGs. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to build the immune-cell-associated prognostic model (ICPM). Kaplan–Meier curve of survival analysis was performed to evaluate the efficacy of the ICPM.

Results

Based on the ESTIMATE and ImmuneAI analysis, we obtained 24 immune cells’ abundance. Next, we identified six coexpression module that was associated with the abundance. Then, LASSO regression models were constructed by selecting the genes in the module that is most relevant to immune cells. Two test dataset was used to testify the model, and we finally, obtained a seven-genes survival model that performed an excellent prognostic efficacy.

Conclusion

In the current study, we filtered seven key genes that may be potential prognostic biomarkers of ESCC, and they may be used as new factors to improve the prognosis of cancer.