Identification of NOTCH4 mutation as a response biomarker for immune checkpoint inhibitor therapy

Notch signaling and cancer: Insights into chemoresistance, immune evasion, and immunotherapy

The Notch signaling pathway is a fundamental and highly conserved cell-to-cell communication system vital for embryonic development and tissue maintenance. However, its dysregulation has been associated with the initiation, progression, and chemoresistance of various cancers. In this comprehensive review, we will take an in-depth look at the multiple roles of the Notch family in cancer pathogenesis, immune response, and resistance to chemotherapy. We delve into the complicated mechanisms by which Notch signaling promotes tumor growth and development, including its influence on TME remodeling and immune evasion strategies. We will also be discussing recent studies that shed light on the connection between cancer stemness and chemoresistance mediated through the activation of Notch signaling pathways. Elucidation of the interplay between the Notch pathway and major constituents of the TME, including immune cells and cancer-associated fibroblasts, is necessary for the development of targeted therapies against Notch-driven tumors. We further discuss the potential of targeting Notch signaling alone or in combination with standard chemotherapy and immunotherapy as a potent strategy to overcome chemoresistance and improve patient outcomes. We conclude by discussing the challenges and future prospects of using Notch signaling as a therapeutic target in cancer treatment, focusing on how precision medicine and combination approaches are important.

Update on the nature of central giant cell granuloma of the jaw with a focus on the aggressive subtype

Central giant cell granuloma (CGCG) is a benign, localised osteolytic lesion of the jaw ​that is categorised into non-aggressive and aggressive subtypes. In contrast to non-aggressive CGCG, aggressive CGCG is characterised by pain, paraesthesia, root resorption, rapid growth, a size of >5 cm, cortical perforation, or recurrence after surgical treatment. However, the nature of CGCG, especially aggressive CGCG, remains unclear. This study was performed to analyse the systematic and comprehensive characteristics of CGCG of the jaw, especially the aggressive subtype, and first explored the genetic variation of aggressive CGCG by whole-exome sequencing. In total, 42 CGCGs were analysed (including 25 non-aggressive and 17 aggressive subtypes). H3F3A mutations were not detected in these CGCGs through immunohistochemistry and Sanger sequencing. The inability to detect H3F3A mutations could help differentiate CGCG from giant cell tumour of bone, indicating the two diseases are not different stages of the same pathological entity. Additionally, fluorescence in situ hybridisation did not reveal USP6 gene rearrangement in CGCG, which could distinguish it from aneurysmal bone cysts, especially the solid type. Therefore, H3F3A mutation and USP6 gene rearrangement detection have great significance in the clinicopathological diagnosis of CGCG of the jaw in terms of their ability to exclude giant cell tumour of bone and aneurysmal bone cyst. Moreover, the whole-exome sequencing data indicated that LRP1B gene abnormalities might be related to the aggressive biological behaviour of CGCG, and that NOTCH4 mutation could be a novel therapeutic target for aggressive CGCG.

Case Report: Lasting complete response to pembrolizumab in mismatch repair-deficient cardiac sarcoma: a genomic characterization

Sarcomas are traditionally considered "cold" tumors with poor response to immunotherapy. However, evidence accumulating over the last years shows that immune checkpoint inhibitors (ICIs) may have a role in selected sarcoma patients according to predictive markers. Here, we report the case of a woman diagnosed with a primary cardiac undifferentiated sarcoma. Following failure of standard first line chemotherapy, high-throughput sequencing (HTS) revealed a high tumor mutational burden (TMB), pathogenic mutations in FAT1 and NOTCH2 and a microsatellite instability (MSI)-associated signature. Immunohistochemistry confirmed mismatch repair-deficiency (MMRd) and abundant CD8+ tumor-infiltrating lymphocytes (TILs), in the absence of tertiary lymphoid structures. The patient was, therefore, treated with the ICI pembrolizumab, reaching a complete response that continues to persist at last follow-up, more than seven years from initial diagnosis and nearly six years from initiation of ICI treatment. This case illustrates the importance of performing HTS in rare sarcomas given the availability of efficient therapies, such as those for tumors displaying high TMB or MMRd/MSI. In agreement with other reports, it supports the contention that MMRd/MSI status and high numbers of TILs are valuable predictive markers of response to immunotherapy in sarcomas.

Global trends and emerging insights in BRAF and MEK inhibitor resistance in melanoma: a bibliometric analysis

Objective

This study aims to perform a comprehensive bibliometric analysis of global research on BRAF and MEK inhibitor resistance in melanoma, identifying key research trends, influential contributors, and emerging themes from 2003 to 2024.

Methods

A systematic search was conducted in the Web of Science Core Collection (WoSCC) database to retrieve publications related to BRAF and MEK inhibitor resistance from 1 January 2003, to 1 September 2024. Bibliometric analyses, including publication trends, citation networks, and keyword co-occurrence patterns, were performed using VOSviewer and CiteSpace. Collaborative networks, co-cited references, and keyword burst analyses were mapped to uncover shifts in research focus and global cooperation.

Results

A total of 3,503 documents, including 2,781 research articles and 722 review papers, were analyzed, highlighting significant growth in this field. The United States, China, and Italy led in publication volume and citation impact, with Harvard University and the University of California System among the top contributing institutions. Research output showed three phases of growth, peaking in 2020. Keyword and co-citation analyses revealed a transition from early focus on BRAF mutations and MAPK pathway activation to recent emphasis on immunotherapy, combination therapies, and non-apoptotic cell death mechanisms like ferroptosis and pyroptosis. These trends reflect the evolving priorities and innovative approaches shaping the field of resistance to BRAF and MEK inhibitors in melanoma.

Conclusion

Research on BRAF and MEK inhibitor resistance has evolved significantly. This analysis provides a strategic framework for future investigations, guiding the development of innovative, multi-modal approaches to improve treatment outcomes for melanoma patients.

Integrated singlecell and bulk RNA-seq analysis identifies a prognostic signature related to inflammation in colorectal cancer

Inflammation can influence the development of CRC as well as immunotherapy and plays a key role in CRC. Therefore, this study aimed to investigate the potential of inflammation-related genes in CRC risk prediction. Inflammation gene models were constructed and validated by combining transcriptomic and single-cell data from TCGA and GEO databases, and the expression of inflammation-related genes was verified by RT-qPCR. We identified two molecular subtypes and three genetic subtypes, two risk subgroups according to median risk values, constructed a prognostic model including thirteen genes (TIMP1, GDF15, UCN, KRT4, POU4F1, NXPH1, SIX2, NPC1L1, KLK12, IGFL1, FOXD1, ASPG, and CYP4F8), and validated the performance of each aspect of the model in an external database. Patients in the high-risk group had worse survival with reduced immune cell infiltration and a greater tumor mutational load. The risk score correlated strongly with the immune checkpoints PD1, PDL1, PDL2, and CTLA4, and it is possible that high-risk patients are more sensitive to treatment involving immune checkpoints. In the single-cell data, GDF15 was most significantly expressed in cancer cell populations. Therefore, we further validated their expression in cells and tissues using qPCR. In summary, we developed a prognostic marker associated with inflammatory genes to provide new directions for subsequent studies and to help clinicians assess the prognosis of CRC patients as well as to develop personalized treatment strategies.

Deep learning to estimate response of concurrent chemoradiotherapy in non-small-cell lung carcinoma

BACKGROUND

Concurrent chemoradiotherapy (CCRT) is a crucial treatment for non-small cell lung carcinoma (NSCLC). However, the use of deep learning (DL) models for predicting the response to CCRT in NSCLC remains unexplored. Therefore, we constructed a DL model for estimating the response to CCRT in NSCLC and explored the associated biological signaling pathways.

METHODS

Overall, 229 patients with NSCLC were recruited from six hospitals. Based on contrast-enhanced computed tomography (CT) images, a three-dimensional ResNet50 algorithm was used to develop a model and validate the performance in predicting response and prognosis. An associated analysis was conducted on CT image visualization, RNA sequencing, and single-cell sequencing.

RESULTS

The DL model exhibited favorable predictive performance, with an area under the curve of 0.86 (95% confidence interval [CI] 0.79-0·92) in the training cohort and 0.84 (95% CI 0.75-0.94) in the validation cohort. The DL model (low score vs. high score) was an independent predictive factor; it was significantly associated with progression-free survival and overall survival in both the training (hazard ratio [HR] = 0.54 [0.36-0.80], P = 0.002; 0.44 [0.28-0.68], P < 0.001) and validation cohorts (HR = 0.46 [0.24-0.88], P = 0.008; 0.30 [0.14-0.60], P < 0.001). The DL model was also positively related to the cell adhesion molecules, the P53 signaling pathway, and natural killer cell-mediated cytotoxicity. Single-cell analysis revealed that differentially expressed genes were enriched in different immune cells.

CONCLUSION

The DL model demonstrated a strong predictive ability for determining the response in patients with NSCLC undergoing CCRT. Our findings contribute to understanding the potential biological mechanisms underlying treatment responses in these patients.

Large-scale whole-exome sequencing analyses identified protein-coding variants associated with immune-mediated diseases in 350,770 adults

The genetic contribution of protein-coding variants to immune-mediated diseases (IMDs) remains underexplored. Through whole exome sequencing of 40 IMDs in 350,770 UK Biobank participants, we identified 162 unique genes in 35 IMDs, among which 124 were novel genes. Several genes, including FLG which is associated with atopic dermatitis and asthma, showed converging evidence from both rare and common variants. 91 genes exerted significant effects on longitudinal outcomes (interquartile range of Hazard Ratio: 1.12-5.89). Mendelian randomization identified five causal genes, of which four were approved drug targets (CDSN, DDR1, LTA, and IL18BP). Proteomic analysis indicated that mutations associated with specific IMDs might also affect protein expression in other IMDs. For example, DXO (celiac disease-related gene) and PSMB9 (alopecia areata-related gene) could modulate CDSN (autoimmune hypothyroidism-, psoriasis-, asthma-, and Graves' disease-related gene) expression. Identified genes predominantly impact immune and biochemical processes, and can be clustered into pathways of immune-related, urate metabolism, and antigen processing. Our findings identified protein-coding variants which are the key to IMDs pathogenesis and provided new insights into tailored innovative therapies.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer

INTRODUCTION

Identifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy.

METHODS

We utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis. Genomic, transcriptomic data from 952 TCGA NSCLC patients, and immunofluorescence (IF) assessment with the local cohort supported mechanism analysis.

RESULTS

Utilizing the random forest algorithm, a 15-gene VAF-related model was established, differentiating patients with durable clinical benefit (DCB) from no durable benefit (NDB). The model demonstrated robust performance, with ROC-AUC values of 0.905, 0.737, and 0.711 across training (n = 313), internal validation (n = 133), and external validation (n = 157) cohorts. Stratification by the model into high- and low-score groups correlated significantly with both progression-free survival (PFS) (training: P < 0.0001, internal validation: P < 0.0001, external validation: P = 0.0066) and overall survival (OS) (n = 341) (P < 0.0001). Notably, the stratification system was independent of PD-L1 (P < 0.0001) and TMB (P < 0.0001). High-score patients exhibited an increased DCB ratio and longer PFS across both PD-L1 and TMB subgroups. Additionally, the high-score group appeared influenced by tobacco exposure, with activated DNA damage response pathways. Whereas, immune/inflammation-related pathways were enriched in the low-score group. Tumor immune microenvironment analyses revealed higher proportions of exhausted/effector memory CD8 + T cells in the high-score group.

CONCLUSIONS

The mutational VAF profile is a promising biomarker for ICI therapy in NSCLC, with enhanced therapeutic stratification and management as a supplement to PD-L1 or TMB.

Signaling pathways in colorectal cancer implications for the target therapies

Colorectal carcinoma (CRC) stands as a pressing global health issue, marked by the unbridled proliferation of immature cells influenced by multifaceted internal and external factors. Numerous studies have explored the intricate mechanisms of tumorigenesis in CRC, with a primary emphasis on signaling pathways, particularly those associated with growth factors and chemokines. However, the sheer diversity of molecular targets introduces complexity into the selection of targeted therapies, posing a significant challenge in achieving treatment precision. The quest for an effective CRC treatment is further complicated by the absence of pathological insights into the mutations or alterations occurring in tumor cells. This study reveals the transfer of signaling from the cell membrane to the nucleus, unveiling recent advancements in this crucial cellular process. By shedding light on this novel dimension, the research enhances our understanding of the molecular intricacies underlying CRC, providing a potential avenue for breakthroughs in targeted therapeutic strategies. In addition, the study comprehensively outlines the potential immune responses incited by the aberrant activation of signaling pathways, with a specific focus on immune cells, cytokines, and their collective impact on the dynamic landscape of drug development. This research not only contributes significantly to advancing CRC treatment and molecular medicine but also lays the groundwork for future breakthroughs and clinical trials, fostering optimism for improved outcomes and refined approaches in combating colorectal carcinoma.

Deep Learning Based on Computed Tomography Predicts Response to Chemoimmunotherapy in Lung Squamous Cell Carcinoma

Non-small-cell lung carcinoma (NSCLC) often carries a dire prognosis. The advent of neoadjuvant chemoimmunotherapy (NCI) has become a promising approach in NSCLC treatment, making the identification of reliable biomarkers for major pathological response (MPR) crucial. This study aimed to devise a deep learning (DL) model to estimate the MPR to NCI in lung squamous cell carcinoma (LUSC) patients and uncover its biological mechanism. We enrolled a cohort of 309 LUSC patients from various medical institutions. A ResNet50 model, trained on contrast-enhanced computed tomography images, was developed, and validated to predict MPR. We examined somatic mutations, genomic data, tumor-infiltrating immune cells, and intra-tumor microorganisms. Post-treatment, 149 (48.22%) patients exhibited MPR. The DL model demonstrated excellent predictive accuracy, evidenced by an area under the receiver operating characteristic curve (AUC) of 0.95 (95% CI: 0.98-1.00) and 0.90 (95% CI: 0.81-0.98) in the first and second validation sets, respectively. Multivariate logistic regression analysis identified the DL model score (low vs. high) as an independent predictor of MPR. The prediction of MPR (P-MPR) correlated with mutations in four genes, as well as gene ontology and pathways tied to immune response and antigen processing and presentation. Analysis also highlighted diversity in immune cells within the tumor microenvironment and in peripheral blood. Moreover, the presence of four distinct bacteria varied among intra-tumor microorganisms. Our DL model proved highly effective in predicting MPR in LUSC patients undergoing NCI, significantly advancing our understanding of the biological mechanisms involved.

GRIN2A mutation is a novel indicator of stratifying beneficiaries of immune checkpoint inhibitors in multiple cancers

Glutamate-NMDAR receptors (GRINs) have been reported to influence cancer immunogenicity; however, the relationship between GRIN alterations and the response to immune checkpoint inhibitors (ICIs) has not been determined. This study combined clinical characteristics and mutational profiles from multiple cohorts to form a discovery cohort (n = 901). The aim of this study was to investigate the correlation between the mutation status of the GRIN gene and the response to ICI therapy. Additionally, an independent ICI-treated cohort from the Memorial Sloan Kettering Cancer Center (MSKCC, N = 1513) was used for validation. Furthermore, this study explored the associations between GRIN2A mutations and intrinsic and extrinsic immunity using multiomics analysis. In the discovery cohort, patients with GRIN2A-MUTs had improved clinical outcomes, as indicated by a higher objective response rate (ORR: 36.8% vs 25.8%, P = 0.020), durable clinical benefit (DCB: 55.2% vs 38.7%, P = 0.005), prolonged progression-free survival (PFS: HR = 0.65; 95% CI 0.49 to 0.87; P = 0.003), and increased overall survival (OS: HR = 0.67; 95% CI 0.50 to 0.89; P = 0.006). Similar results were observed in the validation cohort, in which GRIN2A-MUT patients exhibited a significant improvement in overall survival (HR = 0.66; 95% CI = 0.49 to 0.88; P = 0.005; adjusted P = 0.045). Moreover, patients with GRIN2A-MUTs exhibited an increase in tumor mutational burden, high expression of costimulatory molecules, increased activity of antigen-processing machinery, and infiltration of various immune cells. Additionally, gene sets associated with cell cycle regulation and the interferon response were enriched in GRIN2A-mutated tumors. In conclusion, GRIN2A mutation is a novel biomarker associated with a favorable response to ICIs in multiple cancers.

Notch signaling and targeted therapy in non-small cell lung cancer

The Notch signaling pathway plays pivotal roles in cell proliferation, stemness and invasion of non-small cell lung cancer (NSCLC). The human Notch family consists of four receptors, namely Notch1, Notch2, Notch3, and Notch4. These receptors are transmembrane proteins that play crucial roles in various cellular processes. Notch1 mostly acts as a pro-carcinogenic factor in NSCLC but sometimes acts as a suppressor. Notch2 has been demonstrated to inhibit the growth and progression of NSCLC, whereas Notch3 facilitates these biological behaviors of NSCLC. The role of Notch4 in NSCLC has not been fully elucidated, but it is evident that Notch4 promotes tumor progression. At present, drugs targeting the Notch pathway are being explored for NSCLC therapy, a majority of which are already in the stage of preclinical research and clinical trials, with bright prospects in the clinical treatment of NSCLC.

Novel insights into Notch signaling in tumor immunity: potential targets for cancer immunotherapy

Notch signaling pathway is a highly conserved system of cell-to-cell communication that participates in various biological processes, such as stem cell maintenance, cell fate decision, cell proliferation and death during homeostasis and development. Dysregulation of Notch signaling has been associated with many aspects of cancer biology, such as maintenance of cancer stem-like cells (CSCs), cancer cell metabolism, angiogenesis and tumor immunity. Particularly, Notch signaling can regulate antitumor or pro-tumor immune cells within the tumor microenvironment (TME). Currently, Notch signaling has drawn significant attention in the therapeutic development of cancer treatment. In this review, we focus on the role of Notch signaling pathway in remodeling tumor immune microenvironment. We describe the impact of Notch signaling on the efficacy of cancer immunotherapies. Furthermore, we summarize the results of relevant preclinical and clinical trials of Notch-targeted therapeutics and discuss the challenges in their clinical application in cancer therapy. An improved understanding of the involvement of Notch signaling in tumor immunity will open the door to new options in cancer immunotherapy treatment.

Genomic characterization and immunotherapy for microsatellite instability-high in cholangiocarcinoma

BACKGROUND

Microsatellite instability-high (MSI-H) is a unique genomic status in many cancers. However, its role in the genomic features and immunotherapy in cholangiocarcinoma (CCA) is unclear. This study aimed to systematically investigate the genomic characterization and immunotherapy efficacy of MSI-H patients with CCA.

METHODS

We enrolled 887 patients with CCA in this study. Tumor samples were collected for next-generation sequencing. Differences in genomic alterations between the MSI-H and microsatellite stability (MSS) groups were analyzed. We also investigated the survival of PD-1 inhibitor-based immunotherapy between two groups of 139 patients with advanced CCA.

RESULTS

Differential genetic alterations between the MSI-H and MSS groups included mutations in ARID1A, ACVR2A, TGFBR2, KMT2D, RNF43, and PBRM1 which were enriched in MSI-H groups. Patients with an MSI-H status have a significantly higher tumor mutation burden (TMB) (median 41.7 vs. 3.1 muts/Mb, P < 0.001) and more positive programmed death ligand 1 (PD-L1) expression (37.5% vs. 11.9%, P < 0.001) than those with an MSS status. Among patients receiving PD-1 inhibitor-based therapy, those with MSI-H had a longer median overall survival (OS, hazard ratio (HR) = 0.17, P = 0.001) and progression-free survival (PFS, HR = 0.14, P < 0.001) than patients with MSS. Integrating MSI-H and PD-L1 expression status (combined positive score ≥ 5) could distinguish the efficacy of immunotherapy.

CONCLUSIONS

MSI-H status was associated with a higher TMB value and more positive PD-L1 expression in CCA tumors. Moreover, in patients with advanced CCA who received PD-1 inhibitor-based immunotherapy, MSI-H and positive PD-L1 expression were associated with improved both OS and PFS.

TRIAL REGISTRATION

This study was registered on ClinicalTrials.gov on 07/01/2017 (NCT03892577).

A novel sub-regional radiomics model to predict immunotherapy response in non-small cell lung carcinoma

BACKGROUND

Identifying precise biomarkers of immunotherapy response for non-small cell lung carcinoma (NSCLC) before treatment is challenging. This study aimed to construct and investigate the potential performance of a sub-regional radiomics model (SRRM) as a novel tumor biomarker in predicting the response of patients with NSCLC treated with immune checkpoint inhibitors, and test whether its predictive performance is superior to that of conventional radiomics, tumor mutational burden (TMB) score and programmed death ligand-1 (PD-L1) expression.

METHODS

We categorized 264 patients from retrospective databases of two centers into training (n = 159) and validation (n = 105) cohorts. Radiomic features were extracted from three sub-regions of the tumor region of interest using the K-means method. We extracted 1,896 features from each sub-region, resulting in 5688 features per sample. The least absolute shrinkage and selection operator regression method was used to select sub-regional radiomic features. The SRRM was constructed and validated using the support vector machine algorithm. We used next-generation sequencing to classify patients from the two cohorts into high TMB (≥ 10 muts/Mb) and low TMB (< 10 muts/Mb) groups; immunohistochemistry was performed to assess PD-L1 expression in formalin-fixed, paraffin-embedded tumor sections, with high expression defined as ≥ 50% of tumor cells being positive. Associations between the SRRM and progression-free survival (PFS) and variant genes were assessed.

RESULTS

Eleven sub-regional radiomic features were employed to develop the SRRM. The areas under the receiver operating characteristic curve (AUCs) of the proposed SRRM were 0.90 (95% confidence interval [CI] 0.84-0.96) and 0.86 (95% CI 0.76-0.95) in the training and validation cohorts, respectively. The SRRM (low vs. high; cutoff value = 0.936) was significantly associated with PFS in the training (hazard ratio [HR] = 0.35 [0.24-0.50], P < 0.001) and validation (HR = 0.42 [0.26-0.67], P = 0.001) cohorts. A significant correlation between the SRRM and three variant genes (H3C4, PAX5, and EGFR) was observed. In the validation cohort, the SRRM demonstrated a higher AUC (0.86, P < 0.001) than that for PD-L1 expression (0.66, P = 0.034) and TMB score (0.54, P = 0.552).

CONCLUSIONS

The SRRM had better predictive performance and was superior to conventional radiomics, PD-L1 expression, and TMB score. The SRRM effectively stratified the progression-free survival (PFS) risk among patients with NSCLC receiving immunotherapy.

TG468: a text graph convolutional network for predicting clinical response to immune checkpoint inhibitor therapy

Enhancing cancer treatment efficacy remains a significant challenge in human health. Immunotherapy has witnessed considerable success in recent years as a treatment for tumors. However, due to the heterogeneity of diseases, only a fraction of patients exhibit a positive response to immune checkpoint inhibitor (ICI) therapy. Various single-gene-based biomarkers and tumor mutational burden (TMB) have been proposed for predicting clinical responses to ICI; however, their predictive ability is limited. We propose the utilization of the Text Graph Convolutional Network (GCN) method to comprehensively assess the impact of multiple genes, aiming to improve the predictive capability for ICI response. We developed TG468, a Text GCN model framing drug response prediction as a text classification task. By combining natural language processing (NLP) and graph neural network techniques, TG468 effectively handles sparse and high-dimensional exome sequencing data. As a result, TG468 can distinguish survival time for patients who received ICI therapy and outperforms single gene biomarkers, TMB and some classical machine learning models. Additionally, TG468's prediction results facilitate the identification of immune status differences among specific patient types in the Cancer Genome Atlas dataset, providing a rationale for the model's predictions. Our approach represents a pioneering use of a GCN model to analyze exome data in patients undergoing ICI therapy and offers inspiration for future research using NLP technology to analyze exome sequencing data.

Mechanisms and biomarkers of immune-related adverse events in gastric cancer

Immune-checkpoint inhibitors (ICIs), different from traditional cancer treatment models, have shown unprecedented anti-tumor effects in the past decade, greatly improving the prognosis of many malignant tumors in clinical practice. At present, the most widely used ICIs in clinical immunotherapy for a variety of solid tumors are monoclonal antibodies against cytotoxic T lymphocyte antigen-4 (CTLA-4), programmed cell death protein 1 (PD-1) and their ligand PD-L1. However, tumor patients may induce immune-related adverse events (irAEs) while performing immunotherapy, and irAE is an obstacle to the prospect of ICI treatment. IrAE is a non-specific disease caused by immune system imbalance, which can occur in many tissues and organs. For example, skin, gastrointestinal tract, endocrine system and lung. Although the exact mechanism is not completely clear, related studies have shown that irAE may develop through many ways. Such as excessive activation of autoreactive T cells, excessive release of inflammatory cytokines, elevated levels of autoantibodies, and common antigens between tumors and normal tissues. Considering that the occurrence of severe IrAE not only causes irreversible damage to the patient's body, but also terminates immunotherapy due to immune intolerance. Therefore, accurate identification and screening of sensitive markers of irAE are the main beneficiaries of ICI treatment. Additionally, irAEs usually require specific management, the most common of which are steroids and immunomodulatory therapies. This review aims to summarize the current biomarkers for predicting irAE in gastric cancer and their possible mechanisms.

Determining the prognosis of Lung cancer from mutated genes using a deep learning survival model: a large multi-center study

BACKGROUND

Gene status has become the focus of prognosis prediction. Furthermore, deep learning has frequently been implemented in medical imaging to diagnose, prognosticate, and evaluate treatment responses in patients with cancer. However, few deep learning survival (DLS) models based on mutational genes that are directly associated with patient prognosis in terms of progression-free survival (PFS) or overall survival (OS) have been reported. Additionally, DLS models have not been applied to determine IO-related prognosis based on mutational genes. Herein, we developed a deep learning method to predict the prognosis of patients with lung cancer treated with or without immunotherapy (IO).

METHODS

Samples from 6542 patients from different centers were subjected to genome sequencing. A DLS model based on multi-panels of somatic mutations was trained and validated to predict OS in patients treated without IO and PFS in patients treated with IO.

RESULTS

In patients treated without IO, the DLS model (low vs. high DLS) was trained using the training MSK-MET cohort (HR = 0.241 [0.213-0.273], P < 0.001) and tested in the inter-validation MSK-MET cohort (HR = 0.175 [0.148-0.206], P < 0.001). The DLS model was then validated with the OncoSG, MSK-CSC, and TCGA-LUAD cohorts (HR = 0.420 [0.272-0.649], P < 0.001; HR = 0.550 [0.424-0.714], P < 0.001; HR = 0.215 [0.159-0.291], P < 0.001, respectively). Subsequently, it was fine-tuned and retrained in patients treated with IO. The DLS model (low vs. high DLS) could predict PFS and OS in the MIND, MSKCC, and POPLAR/OAK cohorts (P < 0.001, respectively). Compared with tumor-node-metastasis staging, the COX model, tumor mutational burden, and programmed death-ligand 1 expression, the DLS model had the highest C-index in patients treated with or without IO.

CONCLUSIONS

The DLS model based on mutational genes can robustly predict the prognosis of patients with lung cancer treated with or without IO.

Expanding the role of combined immunochemotherapy and immunoradiotherapy in the management of head and neck cancer (Review)

Immunotherapy has become one of the most promising approaches in tumor therapy, and there are numerous associated clinical trials in China. As an immunosuppressive tumor, head and neck squamous cell carcinoma (HNSCC) carries a high mutation burden, making immune checkpoint inhibitors promising candidates in this field due to their unique mechanism of action. The present review outlines a comprehensive multidisciplinary cancer treatment approach and elaborates on how combining immunochemotherapy and immunoradiotherapy guidelines could enhance clinical efficacy in patients with HNSCC. Furthermore, the present review explores the immunology of HNSCC, current immunotherapeutic strategies to enhance antitumor activity, ongoing clinical trials and the future direction of the current immune landscape in HNSCC. Advanced-stage HNSCC presents with a poor prognosis, low survival rates and minimal improvement in patient survival trends over time. Understanding the potential of immunotherapy and ways to combine it with surgery, chemotherapy and radiotherapy confers good prospects for the management of human papillomavirus (HPV)-positive HNSCC, as well as other HPV-positive malignancies. Understanding the immune system and its effect on HNSCC progression and metastasis will help to uncover novel biomarkers for the selection of patients and to enhance the efficacy of treatments. Further research on why current immune checkpoint inhibitors and targeted drugs are only effective for some patients in the clinic is needed; therefore, further research is required to improve the overall survival of affected patients.

To be, or not to be: the dilemma of immunotherapy for non-small cell lung cancer harboring various driver mutations

INTRODUCTION

Lung cancer is one of primary cancer type with high incidence and mortality, non-small cell lung cancer (NSCLC) is the most common type of lung cncer. For advanced lung cancer, traditional chemotherapy and targeted therapy become difficult to solve the dilemma of further progress. In recent years, with the clinical application of immunotherapy, the therapeutic strategy of lung cancer has changed dramatically. At present, immunotherapy has shown conspicuous efficacy in NSCLC patients with high expression of programmed death-ligand 1 (PD-L1) and high tumor mutational burden (TMB). The discovery of driver mutations brings delightful hope for targeted cancer therapy. However, it remains controversial whether immunotherapy can be used in NSCLC patients with these specific driver mutations.

METHOD

This article summarized the latest research progresses of immunotherapy in advanced NSCLC. We paid close attention to the relevance of various driver mutations and immunotherapy in NSCLC patients, and summarized the predictive effects of several driver mutations and immunotherapy.

RESULTS

The mutations of KRAS, KRAS+TP53, EPHA (especially EPHA5), ZFHX3, ZFHX3+TP53, NOTCH, BRAF and LRP1B+FAT3 have potential to be used as biomarkers to predict the positive effectiveness of immunotherapy. ZFHX3, ZFHX3+TP53, STKII/LKB1+KEAP1+SMARCA4+PBRM1 mutations in LUAD patients get more positive effect in immunotherapy. While the mutations of EGFR, KEAP1, STKII/LKB1+KRAS, EML4-ALK, MET exon 14 skipping mutation, PBRM1, STKII/LKB1+KEAP1+SMARCA4+PBRM1, ERBB2, PIK3CA and RET often indicate poor benefit from immunotherapy.

CONCLUSION

Many gene mutations have been shown to be associated with immunotherapy efficacy. Gene mutations should be combined with PD-L1, TMB, etc. to predict the effect of immunotherapy.

Novel structured ADAM17 small-molecule inhibitor represses ADAM17/Notch pathway activation and the NSCLC cells' resistance to anti-tumour drugs

Background and aims: The outcomes of current treatment for non-small cell lung cancer (NSCLC) are unsatisfactory and development of new and more efficacious therapeutic strategies are required. The Notch pathway, which is necessary for cell survival to avert apoptosis, induces the resistance of cancer cells to antitumour drugs. Notch pathway activation is controlled by the cleavage of Notch proteins/receptors mediated by A disintegrin and metalloproteinase 17 (ADAM17); therefore, ADAM17 is a reliable intervention target for anti-tumour therapy to overcome the drug resistance of cancer cells. This work aims to develop and elucidate the activation of Compound 2b, a novel-structured small-molecule inhibitor of ADAM17, which was designed and developed and its therapeutic efficacy in NSCLC was assessed via multi-assays. Methods and results: A lead compound for a potential inhibitor of ADAM17 was explored via pharmacophore modelling, molecular docking, and biochemical screening. It was augmented by substituting two important chemical groups [R1 and R2 of the quinoxaline-2,3-diamine (its chemical skeleton)]; subsequently, serial homologs of the lead compound were used to obtain anoptimized compound (2b) with high inhibitory activity compared with leading compound against ADAM17 to inhibit the cleavage of Notch proteins and the accumulation of the Notch intracellular domain in the nuclei of NSCLC cells. The inhibitory activity of compound 2b was demonstrated by quantitative polymerase chain reaction and Western blotting. The specificity of compound 2b on ADAM17 was confirmed via point-mutation. Compound 2b enhanced the activation of antitumor drugs on NSCLC cells, in cell lines and nude mice models, by targeting the ADAM17/Notch pathway. Conclusion: Compound 2b may be a promising strategy for NSCLC treatment.

Current Progress on Predictive Biomarkers for Response to Immune Checkpoint Inhibitors in Gastric Cancer: How to Maximize the Immunotherapeutic Benefit?

Gastric cancer is the fifth most prevalent cancer and the fourth leading cause of cancer death globally. Delayed diagnosis and pronounced histological and molecular variations increase the complexity and challenge of treatment. Pharmacotherapy, which for a long time was systemic chemotherapy based on 5-fluorouracil, is the mainstay of management for advanced gastric cancer. Trastuzumab and programmed cell death 1 (PD-1) inhibitors have altered the therapeutic landscape, contributing to noticeably prolonged survivorship in patients with metastatic gastric cancer. However, research has revealed that immunotherapy is only beneficial to some individuals. Biomarkers, such as programmed cell death ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational load (TMB), have been shown to correlate with immune efficacy in numerous studies and are increasingly employed for the selection of patients most likely to respond to immunotherapy. Gut microorganisms, genetic mutations like POLE/POLD1 and NOTCH4, tumor lymphoid infiltrating cells (TILs), and other novel biomarkers have the potential to develop into new predictors. Prospective immunotherapy for gastric cancer should be guided by a biomarker-driven precision management paradigm, and multidimensional or dynamic marker testing could be the way to go.

Genomic alteration profile and PD-L1 expression among different breast cancer subtypes in Chinese population and their correlations

BACKGROUD

There were limitations existing in programmed cell-death ligand 1 (PD-L1) as predictive biomarkers for breast cancer (BC), hence exploring the correlation between PD-L1 levels and other biomarkers in BC may become a very useful therapeutic clinical tool.

METHODS

A total of 301 Chinese patients with different BC subtypes including 47 HR+/HER2+, 185 HR+/HER2-, 38 HR-/HER2+, and 31 triple-negative breast cancer (TNBC) were enrolled in our study. Next-generation sequencing based Yuansu450 gene panel was used for genomic alteration identification and PD-L1 expression was tested using immunohistochemistry.

RESULTS

The most prevalent BC-related mutations were TP53 mutations, followed by mutations in PIK3CA, ERBB2, CDK12, and GATA3 in our Chinese cohort. We found that mutations DDR2 and MYCL were only mutated in HR-/HER2+ subtype, whereas H3-3A and NRAS mutations were only occurred in HR-/HER2- subtype. The percentage of patients with PD-L1-positive expression was higher in patients with HR-/HER2- mainly due to the percentage of PD-L1-high level. Mutational frequencies of TP53, MYC, FAT4, PBRM1, PREX2 were observed to have significant differences among patients with different BC subtypes based on PD-L1 levels. Moreover, a positive correlation was observed between TMB and PD-L1 level in HR+/HER2- subtype, and showed that the proportion of patients with high PD-L1 expression was higher than that of patients with low PD-L1 expression in the HR+/HER2- and HR+/HER2+ cohorts with high Ki67 expression.

CONCLUSIONS

The genomic alterations based on PD-L1 and other biomarkers of different cohorts may provide more possibilities for the treatment of BC with different subtypes.

Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer

Although the tumor-stroma ratio (TSR) has prognostic value in many cancers, the traditional semi-quantitative visual assessment method has inter-observer variability, making it impossible for clinical practice. We aimed to develop a machine learning (ML) algorithm for accurately quantifying TSR in hematoxylin-and-eosin (H&E)-stained whole slide images (WSI) and further investigate its prognostic effect in patients with muscle-invasive bladder cancer (MIBC). We used an optimal cell classifier previously built based on QuPath open-source software and ML algorithm for quantitative calculation of TSR. We retrospectively analyzed data from two independent cohorts to verify the prognostic significance of ML-based TSR in MIBC patients. WSIs from 133 MIBC patients were used as the discovery set to identify the optimal association of TSR with patient survival outcomes. Furthermore, we performed validation in an independent external cohort consisting of 261 MIBC patients. We demonstrated a significant prognostic association of ML-based TSR with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TSR associated with better prognosis. Uni- and multivariate Cox regression analyses showed that TSR was independently associated with overall survival (p < 0.001 for all analyses) after adjusting for clinicopathological factors including age, gender, and pathologic stage. TSR was found to be a strong prognostic factor that was not redundant with the existing staging system in different subgroup analyses (p < 0.05 for all analyses). Finally, the expression of six genes (DACH1, DEEND2A, NOTCH4, DTWD1, TAF6L, and MARCHF5) were significantly associated with TSR, revealing possible potential biological relevance. In conclusion, we developed an ML algorithm based on WSIs of MIBC patients to accurately quantify TSR and demonstrated its prognostic validity for MIBC patients in two independent cohorts. This objective quantitative method allows application in clinical practice while reducing the workload of pathologists. Thus, it might be of significant aid in promoting precise pathology services in MIBC.

Targeting cancer stem cell pathways for lung cancer therapy

PURPOSE OF REVIEW

The unique properties of cancer stem cells (CSCs) make lung cancer untargetable for quite an extended period. The functional mechanism of this cell type has been illustrated step by step. However, the outcomes of lung cancer patients are still lower than expected clinically. The attempts made by scientists to make challenge history against stemness maintenance of lung cancer cells and their druggable targets are worth elucidating.

RECENT FINDINGS

Many agents, including the Bispecific T-cell engager (BiTE) and AMG 119 targeting DLL3-positive cells, are a tremendous breakthrough in the preclinical and clinical treatment of SCLC. More studies focus on targeting CSCs to overcome TKI resistance in NSCLC. The combo targeting of CSC and the immune microenvironment can favor the treatment of lung cancer patients.

SUMMARY

The current review elucidates the characteristics and related regulating pathways of lung CSCs from essential to preclinical research. We retrospectively introduce an update on the clinical development of therapeutics targeting CSC-associated developmental signaling pathways and discuss the opportunities to target CSC-immune interactions in lung cancer.

Targeting immune cell types of tumor microenvironment to overcome resistance to PD-1/PD-L1 blockade in lung cancer

Lung cancer is the common malignant tumor with the highest mortality rate. Lung cancer patients have achieved benefits from immunotherapy, including immune checkpoint inhibitors (ICIs) therapy. Unfortunately, cancer patients acquire adaptive immune resistance, leading to poor prognosis. Tumor microenvironment (TME) has been demonstrated to play a critical role in participating in acquired adaptive immune resistance. TME is associated with molecular heterogeneity of immunotherapy efficacy in lung cancer. In this article, we discuss how immune cell types of TME are correlated with immunotherapy in lung cancer. Moreover, we describe the efficacy of immunotherapy in driven gene mutations in lung cancer, including KRAS, TP53, EGFR, ALK, ROS1, KEAP1, ZFHX3, PTCH1, PAK7, UBE3A, TNF-α, NOTCH, LRP1B, FBXW7, and STK11. We also emphasize that modulation of immune cell types of TME could be a promising strategy for improving adaptive immune resistance in lung cancer.

Tislelizumab Versus Docetaxel in Patients With Previously Treated Advanced NSCLC (RATIONALE-303): A Phase 3, Open-Label, Randomized Controlled Trial

INTRODUCTION

The phase 3 RATIONALE-303 trial (NCT03358875) investigated the efficacy and safety of tislelizumab versus docetaxel in pretreated patients with advanced NSCLC. Here, we report the efficacy and safety results and describe the exploratory biomarker analyses.

METHODS

A total of 805 patients aged more than or equal to 18 years with locally advanced or metastatic squamous or nonsquamous NSCLC were randomized 2:1 to intravenous tislelizumab 200 mg or docetaxel 75 mg/m² every 3 weeks. Co-primary end points were overall survival (OS) in the intent-to-treat (ITT) and programmed death-ligand 1 (PD-L1) tumor cell expression greater than or equal to 25% populations. The exploratory biomarker analyses included PD-L1 expression, tumor mutation burden, and gene expression profile.

RESULTS

At the prespecified interim analysis (August 10, 2020), the co-primary end point of OS in the ITT population was met, with a statistically significant and clinically meaningful improvement in OS with tislelizumab versus docetaxel (median 17.2 versus 11.9 mo, respectively; hazard ratio [HR] = 0.64, p < 0.0001). At the final analysis (July 15, 2021), the other co-primary end point of OS in the PD-L1 tumor cell greater than or equal to 25% population was further met (median 19.3 versus 11.5 mo, respectively; HR = 0.53, p < 0.0001), and OS continued to improve in the ITT population (median 16.9 versus 11.9 mo, respectively, HR = 0.66). Exploratory biomarker analyses revealed the potential association of NOTCH1-4 mutations with improved tislelizumab efficacy for both OS and progression-free survival, whereas tissue tumor mutation burden correlated with progression-free survival benefit, but not OS benefit. No new safety signals were identified.

CONCLUSIONS

Tislelizumab was found to have a significantly improved and long-term clinical benefit in OS versus docetaxel in pretreated patients with advanced NSCLC, regardless of PD-L1 expression.

Co-expression of receptor tyrosine kinases and CD8 T-lymphocyte genes is associated with distinct prognoses, immune cell infiltration patterns and immunogenicity in cancers

Tumor angiogenesis and the immune microenvironment are 2 essential aspects of the tumor microenvironment (TME). The combination of receptor tyrosine kinase (RTK) inhibitor (TKI)-mediated antiangiogenic therapy and CD8 T-lymphocyte-mediated immunotherapy has become an important focus of cancer treatment, with good results for many tumor types. However, the complex regulatory interactions between these 2 treatment strategies have not been elucidated. Therefore, we systematically investigated the association between the RTKs and CD8 T-lymphocyte genes (CD8Ts) across cancers. We comprehensively evaluated alterations in RTK genes across cancers and examined the co-expression of RTKs and CD8Ts using a weighted gene co-expression network analysis. We found that RTKs exhibited extensive genetic alterations across cancers and were significantly related to the activity of cancer hallmark-related pathways. We identified co-expression between the RTKs and CD8Ts. The low co-expression score subtype was associated with significant better clinical benefits and was characterized by a hot immune microenvironment, including more infiltrating immune cells, higher chemokine expression, and stronger immunogenicity, such as the tumor mutation burden and neoantigens. Two immunotherapy cohorts confirmed that patients with low co-expression scores had an inflamed TME phenotype and significant therapeutic advantages. Then, 4 co-expression patterns were identified, with different patterns reflecting different prognoses and immune microenvironments. The RTK^lowCD8T^high group was associated with the best prognosis and immune-activated microenvironment. In summary, the present study indicates co-expression of RTKs and CD8Ts, which supports the potential application of the combination of inhibiting RTKs activity via TKI-targeted therapy and increasing CD8 T cell activity via immunotherapy in the treatment of cancer.

ANK2 as a novel predictive biomarker for immune checkpoint inhibitors and its correlation with antitumor immunity in lung adenocarcinoma

BACKGROUND

Immune checkpoint inhibitors (ICIs) have been shown to significantly improve the survival of patients with advanced lung adenocarcinoma (LUAD). However, only limited proportion of patients could benefit from ICIs. Novel biomarkers with strong predictability are needed for clinicians to maximize the efficacy of ICIs. Our study aimed to identify potential biomarkers predicting ICIs efficacy in LUAD.

METHODS

The Cancer Genome Atlas (TCGA) PanCancer Atlas studies in cBioportal were used to evaluate the mutation frequency of ANK2 across multiple cancers. Clinical and mutational data for LUAD from ICIs-treated cohorts (Hellmann et al. and Rizvi et al.) were collected to explore the correlation between ANK2 mutation and clinical outcomes. In addition, the relationship between ANK2 expression and clinical outcomes was analyzed using LUAD data from TCGA and Gene Expression Omnibus. Furthermore, the impact of ANK2 mutation and expression on the tumor immune microenvironment of LUAD was analyzed using TCGA and TISIDB databases.

RESULTS

Patients with ANK2 mutation benefited more from ICIs. In ICIs-treated cohort, prolonged progression-free survival (PFS) (median PFS: NR (not reached) vs. 5.42 months, HR (hazard ratio) 0.31, 95% CI 0.18-0.54; P = 0.0037), improved complete response rate (17.65% vs. 1.85%, P = 0.0402), and improved objective response rate (64.71% vs. 24.07%, P = 0.0033) were observed in LUAD patients with ANK2 mutation compared to their wild-type counterparts. Regarding ANK2 expression, it was observed that ANK2 expression was decreased in LUAD (P < 0.05) and a higher level of ANK2 expression was associated with longer overall survival (HR 0.69, 95% CI 0.52-0.92; P = 0.012) in TCGA LUAD cohort. Moreover, ANK2 mutation or higher ANK2 expression correlated with enhanced antitumor immunity and "hot" tumor microenvironment in LUAD, which could be potential mechanisms that ANK2 mutation facilitated ICIs therapy and patients with higher ANK2 expression survived longer.

CONCLUSION

Our findings suggest that ANK2 mutation or increased ANK2 expression may serve as a favorable biomarker for the efficacy of ICIs in patients with LUAD.

Fibroblast growth factor receptor family mutations as a predictive biomarker for immune checkpoint inhibitors and its correlation with tumor immune microenvironment in melanoma

BACKGROUND

The emergence of immune checkpoint inhibitors (ICIs) has significantly improved the clinical outcomes of patients with metastatic melanoma. However, survival benefits are only observed in a subset of patients. The fibroblast growth factor receptor (FGFR) family genes are frequently mutated in melanoma, yet their impacts on the efficacy of ICIs remain unclear. Our study aimed to explore the association of FGFR mutations with ICIs efficacy in metastatic melanoma.

METHODS

The Cancer Genome Atlas (TCGA) data (PanCancer Atlas, skin cutaneous melanoma (SKCM), n = 448) in cBioPortal were collected as a TCGA cohort to investigate the association between FGFR mutations and prognosis of melanoma patients. To explore the impact of FGFR mutations on the efficacy of ICIs in melanoma, clinical and tumor whole-exome sequencing (WES) data of four ICI-treated studies from cBioPortal were consolidated as an ICIs-treated cohort. Moreover, the relationship between FGFR mutations and immunogenicity (tumor mutation burden (TMB), neo-antigen load (NAL), mismatch repair (MMR)-related genes and DNA damage repair (DDR)-related genes) of melanoma was evaluated utilizing data from the ICIs-treated cohort. The influence of FGFR mutations on the tumor immune microenvironment (TIME) of melanoma was also analyzed using the TCGA cohort.

RESULTS

In the TCGA cohort, survival in melanoma patients with or without FGFR mutations was nearly equivalent. In the ICIs-treated cohort, patients with FGFR mutations had better survival than those without (median overall survival: 60.00 vs. 31.00 months; hazard ratio: 0.58, 95% CI: 0.42-0.80; P = 0.0051). Besides, the objective response rate was higher for patients harboring FGFR mutations (55.56%) compared to wild-type patients (22.40%) (P = 0.0076). Mechanistically, it was revealed that FGFR mutations correlated with increased immunogenicity (e.g., TMB, NAL, MMR-related gene mutations and DDR-related gene mutations). Meanwhile, FGFR mutant melanoma tended to exhibit an enhanced antitumor TIME compared with its wild-type counterparts.

CONCLUSIONS

Our study demonstrated that FGFR mutations is a promising biomarker in stratifying patients with advanced melanoma who might benefit from ICIs therapy.

Programmed Cell Death-Ligand-1 expression in Bladder Schistosomal Squamous Cell Carcinoma – There’s room for Immune Checkpoint Blockage?

Schistosoma haematobium, the causative agent of urogenital schistosomiasis, is a carcinogen type 1 since 1994. It is strongly associated with bladder squamous-cell carcinoma in endemic regions, where it accounts for 53-69% of bladder-carcinoma cases. This histological subtype is associated with chronic inflammation being more aggressive and resistant to conventional chemo and radiotherapy. Immune-Checkpoint-Blockage (ICB) therapies targeting the Programmed-Cell-Death-Protein-1(PD-1)/Programmed-Cell-Death-Ligand-1(PD-L1) axis showed considerable success in treating advanced bladder urothelial carcinoma. PD-L1 is induced by inflammatory stimuli and expressed in immune and tumor cells. The binding of PD-L1 with PD-1 modulates immune response leading to T-cell exhaustion. PD-L1 presents in several isoforms and its expression is dynamic and can serve as a companion marker for patients’ eligibility, allowing the identification of positive tumors that are more likely to respond to ICB therapy. The high PD-L1 expression in bladder-urothelial-carcinoma and squamous-cell carcinoma may affect further ICB-therapy application and outcomes. In general, divergent histologies are ineligible for therapy. These treatments are expensive and prone to auto-immune side effects and resistance. Thus, biomarkers capable of predicting therapy response are needed. Also, the PD-L1 expression assessment still needs refinement. Studies focused on squamous cell differentiation associated with S. haematobium remain scarce. Furthermore, in low and middle-income-regions, where schistosomiasis is endemic, SCC biomarkers are needed. This mini-review provides an overview of the current literature regarding PD-L1 expression in bladder-squamous-cell-carcinoma and schistosomiasis. It aims to pinpoint future directions, controversies, challenges, and the importance of PD-L1 as a biomarker for diagnosis, disease aggressiveness, and ICB-therapy prognosis in bladder-schistosomal-squamous-cell carcinoma.

PAPPA2 mutation as a novel indicator stratifying beneficiaries of immune checkpoint inhibitors in skin cutaneous melanoma and non-small cell lung cancer

BACKGROUND

Pappalysin 2 (PAPPA2) mutation, occurring most frequently in skin cutaneous melanoma (SKCM) and non-small cell lung cancer (NSCLC), is found to be related to anti-tumour immune response. However, the association between PAPPA2 and the efficacy of immune checkpoint inhibitors (ICIs) therapy remains unknown.

METHODS

To analyse the performance of PAPPA2 mutation as an indicator stratifying beneficiaries of ICIs, seven public cohorts with whole-exome sequencing (WES) data were divided into the NSCLC set (n = 165) and the SKCM set (n = 210). For further validation, 41 NSCLC patients receiving anti-PD-(L)1 treatment were enrolled in China cohort (n = 41). The mechanism was explored based on The Cancer Genome Atlas database (n = 1467).

RESULTS

In the NSCLC set, patients with PAPPA2 mutation (PAPPA2-Mut) demonstrated a significantly superior progress free survival (PFS, hazard ratio [HR], 0.28 [95% CI, 0.14-0.53]; p < 0.001) and objective response rate (ORR, 77.8% vs. 23.2%; p < 0.001) compared to those with wide-type PAPPA2 (PAPPA2-WT), consistent in the SKCM set (overall survival, HR, 0.49 [95% CI: 0.31-0.78], p < 0.001; ORR, 34.1% vs. 16.9%, p = 0.039) and China cohort. Similar results were observed in multivariable models. Accordingly, PAPPA2 mutation exhibited superior performance in predicting ICIs efficacy compared with other published ICIs-related gene mutations, such as EPHA family, MUC16, LRP1B and TTN, etc. In addition, combined utilization of PAPPA2 mutation and tumour mutational burden (TMB) could expand the identification of potential responders to ICIs therapy in both NSCLC set (HR, 0.36 [95% CI: 0.23-0.57], p < 0.001) and SKCM set (HR, 0.51 [95% CI: 0.34-0.76], p < 0.001). Moreover, PAPPA2 mutation was correlated with enhanced anti-tumour immunity including higher activated CD4 memory T cells level, lower Treg cells level, and upregulated DNA damage repair pathways.

CONCLUSIONS

Our findings indicated that PAPPA2 mutation could serve as a novel indicator to stratify beneficiaries from ICIs therapy in NSCLC and SKCM, warranting further prospective studies.

NOTCH4 mutation as predictive biomarker for immunotherapy benefits in NRAS wildtype melanoma

Background

NRAS wildtype melanoma accounts for approximately 80% of melanomas. Previous studies have shown that NRAS wildtype melanoma had higher response rates and better prognoses than NRAS-mutant patients following immunotherapy, while as major actors in tumor cells and tumor microenvironment (TME), the association between NOTCH family genes and response to immunotherapy in NRAS wildtype melanoma remains indistinct.

Objective

We aim to explore whether NOTCH family gene variation is associated with genomic factors in immune checkpoint inhibitor (ICI) response in NRAS wildtype melanoma and with clinical results in these patients.

Method

This research used genomic data of 265 NRAS wildtype ICI-pretreatment samples from five ICI-treated melanoma cohorts to analyze the relationship between NOTCH family gene mutation and the efficacy of ICI therapy.

Results

NRAS wildtype melanomas with NOTCH4-Mut were identified to be associated with prolonged overall survival (OS) in both the discovery (HR: 0.30, 95% CI: 0.11–0.83, P = 0.01) and validation cohorts(HR: 0.21, 95% CI: 0.07–0.68, P = 0.003). Moreover, NOTCH4-Mut melanoma had a superior clinical response in the discovery cohort (ORR, 40.0% vs 13.11%, P = 0.057) and validation cohort (ORR, 68.75% vs 30.07%, P = 0.004). Further exploration found that NOTCH4-Mut tumors had higher tumor mutation burden (TMB) and tumor neoantigen burden (TNB) (P &lt;0.05). NOTCH4-Mut tumors had a significantly increased mutation in the DNA damage response (DDR) pathway. Gene set enrichment analysis revealed NOTCH4-Mut tumor enhanced anti-tumor immunity.

Conclusion

NOTCH4 mutation may promote tumor immunity and serve as a biomarker to predict good immune response in NRAS wildtype melanoma and guide immunotherapeutic responsiveness.

Transcriptional regulatory networks of circulating immune cells in type 1 diabetes: A community knowledgebase

Investigator-generated transcriptomic datasets interrogating circulating immune cell (CIC) gene expression in clinical type 1 diabetes (T1D) have underappreciated re-use value. Here, we repurposed these datasets to create an open science environment for the generation of hypotheses around CIC signaling pathways whose gain or loss of function contributes to T1D pathogenesis. We firstly computed sets of genes that were preferentially induced or repressed in T1D CICs and validated these against community benchmarks. We then inferred and validated signaling node networks regulating expression of these gene sets, as well as differentially expressed genes in the original underlying T1D case:control datasets. In a set of three use cases, we demonstrated how informed integration of these networks with complementary digital resources supports substantive, actionable hypotheses around signaling pathway dysfunction in T1D CICs. Finally, we developed a federated, cloud-based web resource that exposes the entire data matrix for unrestricted access and re-use by the research community.

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Re-use of transcriptomic type 1 diabetes (T1D) circulating immune cells (CICs) datasets

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We generated transcriptional regulatory networks for T1D CICs

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Use cases generate substantive hypotheses around signaling pathway dysfunction in T1D CICs

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Networks are freely accessible on the web for re-use by the research community

TP53 and LRP1B Co-Wild Predicts Improved Survival for Patients with LUSC Receiving Anti-PD-L1 Immunotherapy

Immunotherapy brought long-term benefits for partial patients with lung squamous cell carcinoma (LUSC). The predictor of anti-PD-L1 therapy was controversial and limited in LUSC. We aimed to explore novel biomarker for LUSC immunotherapy and the potential mechanism. Five hundred and twenty-five Chinese patients (Geneplus cohort) with LUSC underwent targeted sequencing and were involved to explore the genomic profiling. TP53 and LRP1B were the most frequently recurrent genes and correlated to higher tumor mutational burden (TMB). We observed that LUSC patients with TP53 and LRP1B co-wild (co-wild type) were associated with better survival of anti-PD-L1 therapy compared with TP53 mutant or LRP1B mutant (mutant type) in POPAR/OAK cohort. Copy-number variation (CNV) and whole genome doubling (WGD) data from TCGA LUSC cohort were obtained to assess the CNV events. There were fewer CNV alterations and lower chromosome instability in patients with TP53/LRP1B co-wild compared with those with TP53/LRP1B mutant. RNA expression data from the TCGA LUSC cohort were collected to explore the differences in RNA expression and tumor immune microenvironment (TIME) between mutant and co-wild groups. The TP53/LRP1B co-wild type had a significantly increased proportion of multiple tumor-infiltrating lymphocytes (TILs), including activated CD8 T cell, activated dendritic cell (DC), and effector memory CD8 T cell. Immune-related gene sets including checkpoint, chemokine, immunostimulatory, MHC and receptors were enriched in the co-wild type. In conclusion, TP53/LRP1B co-wild LUSC conferred an elevated response rate in anti-PD-L1 therapy and improved survival, which was associated with a chromosome-stable phenotype and an activated immune microenvironment.

Efficacy comparison of immune treating strategies for NSCLC patients with negative PD-L1 expression

BACKGROUND

We intended to compare and grade the proposed immune treating strategies for non-small cell lung cancer (NSCLC) with negative Programmed Cell Death Ligand 1(PD-L1).

METHODS

We compared the efficacy of single immune checkpoint inhibitor (ICI), single ICI plus chemotherapy, and doublet ICIs with chemotherapy alone, as well as single ICI plus radiotherapy with single ICI for negative PD-L1 (<1%) NSCLC patients. Hazard Ratio (HR) and 95% confidence interval (CI) of progression-free survival (PFS) and overall survival (OS) were used as outcomes.

RESULTS

We included 23 randomized control trials with 4665 patients. Compared with chemotherapy alone, single ICI, single ICI plus chemotherapy and doublet ICIs all showed a better OS (0.84 [0.71, 0.99] ; 0.77 [0.69, 0.85] ; 0.64 [0.53, 0.77])), while single ICI plus chemotherapy and doublet ICIs showed a better PFS (0.68 [0.61, 0.75] ; 0.69 [0.56, 0.85]). Additionally, single ICI plus radiotherapy obtained a greater pooled PFS (0.49 [0.28-0.87]) than single ICI.

CONCLUSIONS

Both single ICI plus chemotherapy and doublet ICIs were probably better treatment decisions than chemotherapy alone for negative PD-L1 NSCLC patients. Also, single ICI plus radiotherapy carved out a new strategy.

Roles of Notch Signaling in the Tumor Microenvironment

The Notch signaling pathway is an architecturally simple signaling mechanism, well known for its role in cell fate regulation during organ development and in tissue homeostasis. In keeping with its importance for normal development, dysregulation of Notch signaling is increasingly associated with different types of tumors, and proteins in the Notch signaling pathway can act as oncogenes or tumor suppressors, depending on the cellular context and tumor type. In addition to a role as a driver of tumor initiation and progression in the tumor cells carrying oncogenic mutations, it is an emerging realization that Notch signaling also plays a role in non-mutated cells in the tumor microenvironment. In this review, we discuss how aberrant Notch signaling can affect three types of cells in the tumor stroma-cancer-associated fibroblasts, immune cells and vascular cells-and how this influences their interactions with the tumor cells. Insights into the roles of Notch in cells of the tumor environment and the impact on tumor-stroma interactions will lead to a deeper understanding of Notch signaling in cancer and inspire new strategies for Notch-based tumor therapy.

Shooting at Moving and Hidden Targets-Tumour Cell Plasticity and the Notch Signalling Pathway in Head and Neck Squamous Cell Carcinomas

Head and Neck Squamous Cell Carcinoma (HNSCC) is often aggressive, with poor response to current therapies in approximately 40-50% of the patients. Current therapies are restricted to operation and irradiation, often combined with a small number of standard-of-care chemotherapeutic drugs, preferentially for advanced tumour patients. Only very recently, newer targeted therapies have entered the clinics, including Cetuximab, which targets the EGF receptor (EGFR), and several immune checkpoint inhibitors targeting the immune receptor PD-1 and its ligand PD-L1. HNSCC tumour tissues are characterized by a high degree of intra-tumour heterogeneity (ITH), and non-genetic alterations that may affect both non-transformed cells, such as cancer-associated fibroblasts (CAFs), and transformed carcinoma cells. This very high degree of heterogeneity likely contributes to acquired drug resistance, tumour dormancy, relapse, and distant or lymph node metastasis. ITH, in turn, is likely promoted by pronounced tumour cell plasticity, which manifests in highly dynamic and reversible phenomena such as of partial or hybrid forms of epithelial-to-mesenchymal transition (EMT), and enhanced tumour stemness. Stemness and tumour cell plasticity are strongly promoted by Notch signalling, which remains poorly understood especially in HNSCC. Here, we aim to elucidate how Notch signal may act both as a tumour suppressor and proto-oncogenic, probably during different stages of tumour cell initiation and progression. Notch signalling also interacts with numerous other signalling pathways, that may also have a decisive impact on tumour cell plasticity, acquired radio/chemoresistance, and metastatic progression of HNSCC. We outline the current stage of research related to Notch signalling, and how this pathway may be intricately interconnected with other, druggable targets and signalling mechanisms in HNSCC.