Improvement of PD-1 Blockade Efficacy and Elimination of Immune-Related Gastrointestinal Adverse Effect by mTOR Inhibitor

Spontaneous Hydropneumothorax After Pleurodesis in a Patient With Pulmonary Lymphangioleiomyomatosis With Associated Endometrial Cancer

Lymphangioleiomyomatosis (LAM) is a rare cystic disease that occurs due to the abnormal proliferation of smooth muscle-like cells. It primarily affects the lungs but can also have extrapulmonary manifestations such as lymphangioleiomyoma and angiomyolipomas. It is more common in young women of childbearing age, with female sex hormones contributing to the disease course. LAM can develop either through sporadic mutations or through genetic inheritance of the tuberous sclerosis complex (TSC) genes. TSC, LAM, and endometrial cancer are associated with mTOR pathway activation, which can explain why these diseases can co-exist, although the co-existence of LAM and endometrial cancer in the same patient is very rare. Due to the cystic nature of LAM, pneumothorax most often occurs at least once during the course of the disease, and most times, it is the first manifestation observed in LAM. These patients are also at high risk for recurrent pneumothorax, and when that occurs, pleurodesis is indicated. Unfortunately, pleurodesis still does not preclude a pneumothorax from occurring. We present the case of a female patient with LAM and endometrial cancer who was found to have an incidental spontaneous hydropneumothorax after pleurodesis. Patients with LAM should be closely monitored for the possible development of other mTOR-associated diseases. Moreover, when performing pleurodesis for recurrent pneumothorax in very high-risk patients, the procedure with the lowest recurrence rate should be utilized.

IFN-γ decreases PD-1 in T lymphocytes from convalescent COVID-19 patients via the AKT/GSK3β signaling pathway

Post-COVID-19 syndrome may be associated with the abnormal immune status. Compared with the unexposed age-matched elder group, PD-1 in the CD8+ T cells from recovered COVID-19 patients was significantly lower. IFN-γ in the plasma of COVID-19 convalescent patients was increased, which inhibited PD-1 expression in CD8+ T cells from COVID-19 convalescent patients. scRNA-seq bioinformatics analysis revealed that AKT/GSK3β may regulate the INF-γ/PD-1 axis in CD8+ T cells from COVID-19 convalescent patients. In parallel, an IFN-γ neutralizing antibody reduced AKT and increased GSK3β in PBMCs. An AKT agonist (SC79) significantly decreased p-GSK3β. Moreover, AKT decreased PD-1 on CD8+ T cells, and GSK3β increased PD-1 on CD8+ T cells according to flow cytometry analysis. Collectively, we demonstrated that recovered COVID-19 patients may develop long COVID. Increased IFN-γ in the plasma of recovered Wuhan COVID-19 patients contributed to PD-1 downregulation on CD8+ T cells by regulating the AKT/GSK3β signaling pathway.

Constructing heterogeneous single-cell landscape and identifying microenvironment molecular characteristics of primary and lymphatic metastatic head and neck squamous cell carcinoma

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) accounts for more than half of head and neck tumors, roughly 90%. This study focused on constructing the heterogeneous landscape using single-cell and bulk transcriptomic data to identify molecular characteristics of the microenvironment in primary and lymphatic metastatic head and neck squamous carcinomas.

METHOD

The study enrolled 23 HNSCC samples with scRNA-seq data and 546 HNSCC samples from TCGA. We used Monocle to sort the cells and used CellPhoneDB to explore the cell-cell interactions. Infercnv, which was used to infer cells with apparent copy number variation based on single-cell sequencing transcriptome data. We re-evaluated HNSCC bulk RNA transcriptome data to characterize the functions of different cell types in shaping the immune microenvironment of HNSCC.

RESULTS

We combined genealogical reconstruction, CNV inference, and cellular interactions to uncover the characteristics of distinct cell populations in different disease states, differences in cancer and immune cell lineages of differentiation trajectories, and interactions between non-immune and immune cell. PD-1 and PD-L1/PD-L2 expressed extremely rare in T cells, the immune checkpoint molecule KLRB1-CLEC2D achieved a high-level expression. We identified three microenvironment-based HNSCC subtypes associated with the prognosis of HNSCC patients.

CONCLUSIONS

In summary, the present study dissected the intratumoral heterogeneity and immune microenvironment of primary and metastatic HNSCC, which is crucial to reveal the mechanisms of resistance to immunotherapy in HNSCC in different disease states and is expected to assist in the further investigation of the mechanism of HNSCC cell metastasis and guide the treatment of clinical patients.

Stocking the toolbox-Using preclinical models to understand the development and treatment of immune checkpoint inhibitor-induced immune-related adverse events

Cancer patients treated with immune checkpoint inhibitors (ICIs) are susceptible to a broad and variable array of immune-related adverse events (irAEs). With increasing clinical use of ICIs, defining the mechanism for irAE development is more critical than ever. However, it currently remains challenging to predict when these irAEs occur and which organ may be affected, and for many of the more severe irAEs, inaccessibility to the tissue site hampers mechanistic insight. This lack of understanding of irAE development in the clinical setting emphasizes the need for greater use of preclinical models that allow for improved prediction of biomarkers for ICI-initiated irAEs or that validate treatment options that inhibit irAEs without hampering the anti-tumor immune response. Here, we discuss the utility of preclinical models, ranging from exploring databases to in vivo animal models, focusing on where they are most useful and where they could be improved.

Immunosuppression for immune-related adverse events during checkpoint inhibition: an intricate balance

Immune checkpoint inhibitors (ICIs) have changed perspectives for patients with cancer, but come with severe immune-related adverse events (irAEs). To prevent fatality or chronicity, these irAEs are often promptly treated with high-dose immunosuppressants. Until recently, evidence on the effects of irAE management on ICI efficacy has been sparse. As a result, algorithms for irAE management are mostly expert-opinion based and barely consider possible detrimental effects of immunosuppressants on ICI efficacy. However, recent growing evidence suggests that vigorous immunosuppressive management of irAEs comes with unfavourable effects on ICI efficacy and survival. With expansion of the indications of ICIs, evidence-based treatment of irAEs without hampering tumour control becomes more and more important. In this review, we discuss novel evidence from pre-clinical and clinical studies on the effects of different irAE management regimens including corticosteroids, TNF inhibition and tocilizumab on cancer control and survival. We provide recommendations for pre-clinical research, cohort studies and clinical trials that can help clinicians in tailored irAE management, minimising patients' burden while maintaining ICI efficacy.

Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy

The emergence of immunotherapy has dramatically changed the cancer treatment paradigm and generated tremendous promise in precision medicine. However, cancer immunotherapy is greatly limited by its low response rates and immune-related adverse events. Transcriptomics technology is a promising tool for deciphering the molecular underpinnings of immunotherapy response and therapeutic toxicity. In particular, applying single-cell RNA-seq (scRNA-seq) has deepened our understanding of tumor heterogeneity and the microenvironment, providing powerful help for developing new immunotherapy strategies. Artificial intelligence (AI) technology in transcriptome analysis meets the need for efficient handling and robust results. Specifically, it further extends the application scope of transcriptomic technologies in cancer research. AI-assisted transcriptomic analysis has performed well in exploring the underlying mechanisms of drug resistance and immunotherapy toxicity and predicting therapeutic response, with profound significance in cancer treatment. In this review, we summarized emerging AI-assisted transcriptomic technologies. We then highlighted new insights into cancer immunotherapy based on AI-assisted transcriptomic analysis, focusing on tumor heterogeneity, the tumor microenvironment, immune-related adverse event pathogenesis, drug resistance, and new target discovery. This review summarizes solid evidence for immunotherapy research, which might help the cancer research community overcome the challenges faced by immunotherapy.

Neutrophil extracellular traps (NETs)-related lncRNAs signature for predicting prognosis and the immune microenvironment in breast cancer

Background: Neutrophil extracellular traps (NETs) are closely associated to tumorigenesis and development. However, the relationship between NETs-related long non-coding RNAs (lncRNAs) and the characteristics of breast tumor remains an enigma. This study aimed to explore the clinical prognostic value of NETs-related lncRNAs, their correlation with the tumor microenvironment (TME) and their predictive ability of drug sensitivity in patients with breast cancer (BC). Methods: The expression profiles of RNA-sequencing and relevant clinical data of BC patients were extracted from TCGA database. The co-expression network analysis, univariable, least absolute shrinkage and selection operator (LASSO) and multivariable Cox algorithms were employed to construct the NETs-related lncRNAs signature. A nomogram was established and validated to explore the clinical application. Furthermore, the immune microenvironment and drug sensitivity for BC with different prognostic risks were explored. Finally, the expression pattern of lncRNAs was validated using qRT-PCR in BC tissues and their adjacent non-cancerous tissues. Results: Based on NETs-related lncRNAs, a prognostic risk model consisted of 10 lncRNAs (SFTA1P, ACTA2-AS1, AC004816.2, AC000067.1, LINC01235, LINC01010, AL133467.1, AC092919.1, AL591468.1, and MIR200CHG) was established. The Kaplan-Meier analysis showed that the overall survival (OS) was significantly better in low-risk BC patients than in high-risk BC patients (P _{training cohort} < 0.001, P _{validation cohort} = 0.009). The nomogram also showed good predictive accuracy for OS of BC individuals in both training and validation cohorts. The function enrichment analysis revealed that high-risk group was mainly enriched in immune-related functions and pathways, and the tumor mutation burden in this group was markedly higher than that in the low-risk group (p = 0.022). Moreover, significant differences were observed in immune cells, immune functions and immune checkpoint genes among BC patients at different risks (p < 0.05). The response to chemotherapeutic agents and immunotherapy were also closely related with the expression of NETs-related lncRNAs (p < 0.001). The expression of lncRNAs from experimental validation were generally consistent with the bioinformatics analysis results. Conclusion: Our study provided a novel prognostic model for BC and yielded strong scientific rationale for individualized treatment strategies, elucidating immunotherapy in BC patients.

Genetic dysregulation of immunologic and oncogenic signaling pathways associated with tumor-intrinsic immune resistance: a molecular basis for combination targeted therapy-immunotherapy for cancer

Since the turn of the century, advances in targeted therapy and immunotherapy have revolutionized the treatment of cancer. Although these approaches have far outperformed traditional therapies in various clinical settings, both remain plagued by mechanisms of innate and acquired resistance that limit therapeutic efficacy in many patients. With a focus on tumor-intrinsic resistance to immunotherapy, this review highlights our current understanding of the immunologic and oncogenic pathways whose genetic dysregulation in cancer cells enables immune escape. Emphasis is placed on genomic, epigenomic, transcriptomic, and proteomic aberrations that influence the activity of these pathways in the context of immune resistance. Specifically, the role of pathways that govern interferon signaling, antigen processing and presentation, and immunologic cell death as determinants of tumor immune susceptibility are discussed. Likewise, mechanisms of tumor immune resistance mediated by dysregulated RAS-MAPK, WNT, PI3K-AKT-mTOR, and cell cycle pathways are described. Finally, this review highlights the ways in which recent insight into genetic dysregulation of these immunologic and oncogenic signaling pathways is informing the design of combination targeted therapy-immunotherapy regimens that aim to restore immune susceptibility of cancer cells by overcoming resistance mechanisms that often limit the success of monotherapies.

Immunotherapy for hepatocellular carcinoma recurrence after liver transplantation, can we harness the power of immune checkpoint inhibitors?

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer-related death globally and liver transplantation (LT) can serve as the best curative treatment option. However, HCC recurrence after LT remains the major obstacle to the long-term survival of recipients. Recently, immune checkpoint inhibitors (ICIs) have revolutionized the treatment of many cancers and provided a new treatment strategy for post-LT HCC recurrence. Evidence has been accumulated with the real-world application of ICIs in patients with post-LT HCC recurrence. Notably, the use of these agents as immunity boosters in recipients treated with immunosuppressors is still controversial. In this review, we summarized the immunotherapy for post-LT HCC recurrence and conducted an efficacy and safety evaluation based on the current experience of ICIs for post-LT HCC recurrence. In addition, we further discussed the potential mechanism of ICIs and immunosuppressive agents in regulating the balance between immune immunosuppression and lasting anti-tumor immunity.

Immune-related pulmonary toxicities of checkpoint inhibitors in non-small cell lung cancer: Diagnosis, mechanism, and treatment strategies

Immune checkpoint inhibitors (ICI) therapy based on programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1) has changed the treatment paradigm of advanced non-small cell lung cancer (NSCLC) and improved the survival expectancy of patients. However, it also leads to immune-related adverse events (iRAEs), which result in multiple organ damage. Among them, the most common one with the highest mortality in NSCLC patients treated with ICI is checkpoint inhibitor pneumonitis (CIP). The respiratory signs of CIP are highly coincident and overlap with those in primary lung cancer, which causes difficulties in detecting, diagnosing, managing, and treating. In clinical management, patients with serious CIP should receive immunosuppressive treatment and even discontinue immunotherapy, which impairs the clinical benefits of ICIs and potentially results in tumor recrudesce. Therefore, accurate diagnosis, detailedly dissecting the pathogenesis, and developing reasonable treatment strategies for CIP are essential to prolong patient survival and expand the application of ICI. Herein, we first summarized the diagnosis strategies of CIP in NSCLC, including the classical radiology examination and the rising serological test, pathology test, and artificial intelligence aids. Then, we dissected the potential pathogenic mechanisms of CIP, including disordered T cell subsets, the increase of autoantibodies, cross-antigens reactivity, and the potential role of other immune cells. Moreover, we explored therapeutic approaches beyond first-line steroid therapy and future direction based on targeted signaling pathways. Finally, we discussed the current impediments, future trends, and challenges in fighting ICI-related pneumonitis.

Correlation between IL3 signaling pathway-related genes and immune checkpoint inhibitor efficacy in patients with renal cell carcinoma

BACKGROUND

There is a lack of effective biomarkers that predict immunotherapy efficacy in clear cell renal cell carcinoma(KIRC).

OBJECTIVE

We aimed to identify biomarkers that would predict the efficacy of KIRC treatment with immune checkpoint inhibitors (ICIs).

METHODS

Cohort data of KIRC patients with somatic mutations, mRNA expression and survival data from The Cancer Genome Atlas (TCGA) database and immunotherapy cohort and Genomics of Drug Sensitivity in Cancer (GDSC) database were analyzed and divided into interleukin 3 (IL3) pathway-related genes high expression (IL3-High) and IL3 pathway-related genes low expression (IL3-Low) groups according to pathway expression status to assess the relationship between the IL3 pathway-related genes activation status and the prognosis of KIRC patients treated with ICIs. The data were validated by immunohistochemistry experiments, and possible mechanisms of action were explored at the level of gene mutation landscape, immune microenvironment characteristics, transcriptome and copy number variation(CNV) characteristicsRESULTS: The IL3 pathway-related genes was an independent predictor of the efficacy of ICIs in KIRC patients, and the IL3-High group had a longer overall survival (OS); KIRC patients in the IL3-High group had increased levels of chemokines, cytolysis, immune checkpoint gene expression and abundant immunity. The IL3-Low group had poor immune cell infiltration and significant downregulation of complement activation, cytophagy, B-cell activation, and humoral immune response pathways. The high group was more sensitive to targeted drugs of some signaling pathways, and its efficacy in combining these drugs with immunity has been predicted in the published literature.

CONCLUSION

The IL3 pathway-related genes can be used as a predictor of the efficacy of ICIs in KIRC. The IL3 pathway-related genes may affect the therapeutic efficacy of ICIs by affecting the expression of immune-related molecules, immune cell infiltration, and the level of immune response pathways.

Tumor cell-derived exosomal lncRNA LOC441178 inhibits the tumorigenesis of esophageal carcinoma through suppressing macrophage M2 polarization

Esophageal carcinoma (EC) is a highly malignant type of tumor. In a previous study, the authors found that long non-coding RNA (lncRNA) LOC441178 inhibited the tumorigenesis of EC. Moreover, exosomes derived from tumor cells containing lncRNAs were found to play a key role in the tumor environment; however, whether exosomes can affect the tumor microenvironment by carrying LOC441178 remains unclear. Thus, the present study aimed to clarify this. In order to assess the effects of exosomal LOC441178 in EC, cell invasion and migration were examined using the Transwell assay. Exosomes were identified using transmission electron microscopy, Western blot analysis and nanoparticle tracking analysis. Furthermore, macrophage surface makers (CD206 and CD86) were analyzed using flow cytometry. Moreover, a subcutaneous xenograft mouse model was constructed to assess the role of TE-9 cells-derived exosomal LOC441178 in EC. The results revealed that LOC441178 overexpression notably suppressed the metastasis of EC cells. In addition, exosomes were successfully isolated from EC cells, and LOC441178 level was upregulated in exosomes derived from LOC441178- overexpressed EC cells. Exosomal LOC441178 also suppressed macrophage M2 polarization, and the polarized macrophages decreased EC cell invasion. Exosomes containing LOC441178 notably inhibited the growth of EC in mice. On the whole, the present study demonstrated that the delivery of LOC441178 by EC cell-secreted exosomes inhibited the tumorigenesis of EC by suppressing the polarization of M2 macrophages. These findings may provide a new theoretical basis for discovering new strategies against EC.

Loss of MHC-I antigen presentation correlated with immune checkpoint blockade tolerance in MAPK inhibitor-resistant melanoma

Immune checkpoint blockade and MAPK-targeted combined therapy is a promising regimen for advanced melanoma patients. However, the clinical benefit from this combo regimen remains limited, especially in patients who acquired resistance to MAPK-targeted therapy. Here, we systematically characterized the immune landscape during MAPK-targeted therapy in patients and mouse melanoma models. We observed that both the abundance of tumor-infiltrated T cells and the expression of immune-related genes were upregulated in the drug-responsive period, but downregulated in the resistance period, implying that acquired drug resistance dampens the antitumor immune response. Further transcriptomic dissection indicated that loss of MHC-I antigen presentation on tumor cells plays a critical role in the reduction of T cell infiltration during drug resistance. Survival analysis demonstrates that loss of antigen presentation and reduction of T-cell infiltration during acquired drug resistance are associated with poorer clinical response and prognosis of anti-PD-1 therapy in melanoma patients. In addition, we identified that alterations in the MAPK inhibitor resistance-related oncogenic signaling pathway closely correlated with deficiency of MHC-I antigen presentation, including activation of the PI3K-mTOR, MAPK, and Wnt pathways. In conclusion, our research illuminates that decreased infiltration of T cells is associated with acquired drug resistance during MAPK-targeted therapy, which may underlie the cross-resistance to immune checkpoint blockade.

Crosstalk Between Metabolism and Immune Activity Reveals Four Subtypes With Therapeutic Implications in Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is characterized by metabolic dysregulation and distinct immunological signatures. The interplay between metabolic and immune processes in the tumor microenvironment (TME) causes the complexity and heterogeneity of immunotherapy responses observed during ccRCC treatment. Herein, we initially identified two distinct metabolic subtypes (C1 and C2 subtypes) and immune subtypes (I1 and I2 subtypes) based on the occurrence of differentially expressed metabolism-related prognostic genes and immune-related components. Notably, we observed that immune regulators with upregulated expression actively participated in multiple metabolic pathways. Therefore, we further delineated four immunometabolism-based ccRCC subtypes (M1, M2, M3, and M4 subtypes) according to the results of the above classification. Generally, we found that high metabolic activity could suppress immune infiltration. Immunometabolism subtype classification was associated with immunotherapy response, with patients possessing the immune-inflamed, metabolic-desert subtype (M3 subtype) that benefits the most from immunotherapy. Moreover, differences in the shifts in the immunometabolism subtype after immunotherapy were observed in the responder and non-responder groups, with patients from the responder group transferring to subtypes with immune-inflamed characteristics and less active metabolic activity (M3 or M4 subtype). Immunometabolism subtypes could also serve as biomarkers for predicting immunotherapy response. To decipher the genomic and epigenomic features of the four subtypes, we analyzed multiomics data, including miRNA expression, DNA methylation status, copy number variations occurrence, and somatic mutation profiles. Patients with the M2 subtype possessed the highest VHL gene mutation rates and were more likely to be sensitive to sunitinib therapy. Moreover, we developed non-invasive radiomic models to reveal the status of immune activity and metabolism. In addition, we constructed a radiomic prognostic score (PRS) for predicting ccRCC survival based on the seven radiomic features. PRS was further demonstrated to be closely linked to immunometabolism subtype classification, immune score, and tumor mutation burden. The prognostic value of the PRS and the association of the PRS with immune activity and metabolism were validated in our cohort. Overall, our study established four immunometabolism subtypes, thereby revealing the crosstalk between immune and metabolic activities and providing new insights into personal therapy selection.