Molecular and genetic properties of tumors associated with local immune cytolytic activity

Immune regulation and the tumor microenvironment in anti-PD-1/PDL-1 and anti-CTLA-4 therapies for cancer immune evasion: A bibliometric analysis

This study aims to conduct a bibliometric analysis, employing visualization tools to examine literature pertaining to tumor immune evasion related to anti-CTLA-4 and anti-PD-1/PD-L1 therapy from 1999 to 2022. A special emphasis is placed on the interplay between tumor microenvironment, signaling pathways, immune cells and immune evasion, with data sourced from the Web of Science core collection (WoSCC). Advanced tools, including VOSviewer, Citespace, and Scimago Graphica, were utilized to analyze various parameters, such as co-authorship/co-citation patterns, regional contributions, journal preferences, keyword co-occurrences, and significant citation bursts. Out of 4778 publications reviewed, there was a marked increase in research focusing on immune evasion, with bladder cancer being notably prominent. Geographically, China, the USA, and Japan were the leading contributors. Prestigious institutions like MD Anderson Cancer Center, Harvard Medical School, Fudan University, and Sun Yat Sen University emerged as major players. Renowned journals in this domain included Frontiers in Immunology, Cancers, and Frontiers in Oncology. Ehen LP and Wang W were identified as prolific authors on this topic, while Topalian SL stood out as one of the most cited. Research current situation is notably pivoting toward challenges like immunotherapy resistance and the intricate signaling pathways driving drug resistance. This bibliometric study seeks to provide a comprehensive overview of past and current research trends, emphasizing the potential role of tumor microenvironment, signaling pathways and immune cells in the context of immune checkpoint inhibitors (ICIs) and tumor immune evasion.

Mime: A flexible machine-learning framework to construct and visualize models for clinical characteristics prediction and feature selection

The widespread use of high-throughput sequencing technologies has revolutionized the understanding of biology and cancer heterogeneity. Recently, several machine-learning models based on transcriptional data have been developed to accurately predict patients' outcome and clinical response. However, an open-source R package covering state-of-the-art machine-learning algorithms for user-friendly access has yet to be developed. Thus, we proposed a flexible computational framework to construct a machine learning-based integration model with elegant performance (Mime). Mime streamlines the process of developing predictive models with high accuracy, leveraging complex datasets to identify critical genes associated with prognosis. An in silico combined model based on de novo PIEZO1-associated signatures constructed by Mime demonstrated high accuracy in predicting the outcomes of patients compared with other published models. Furthermore, the PIEZO1-associated signatures could also precisely infer immunotherapy response by applying different algorithms in Mime. Finally, SDC1 selected from the PIEZO1-associated signatures demonstrated high potential as a glioma target. Taken together, our package provides a user-friendly solution for constructing machine learning-based integration models and will be greatly expanded to provide valuable insights into current fields. The Mime package is available on GitHub (https://github.com/l-magnificence/Mime).

DNA methylation heterogeneity attributable to a complex tumor immune microenvironment prompts prognostic risk in glioma

Gliomas are malignant tumours of the human nervous system with different World Health Organization (WHO) classifications, glioblastoma (GBM) with higher grade and are more malignant than lower-grade glioma (LGG). To dissect how the DNA methylation heterogeneity in gliomas is influenced by the complex cellular composition of the tumour immune microenvironment, we first compared the DNA methylation profiles of purified human immune cells and bulk glioma tissue, stratifying three tumour immune microenvironmental subtypes for GBM and LGG samples from The Cancer Genome Atlas (TCGA). We found that more intermediate methylation sites were enriched in glioma tumour tissues, and used the Proportion of sites with Intermediate Methylation (PIM) to compare intertumoral DNA methylation heterogeneity. A larger PIM score reflected stronger DNA methylation heterogeneity. Enhanced DNA methylation heterogeneity was associated with stronger immune cell infiltration, better survival rates, and slower tumour progression in glioma patients. We then created a Cell-type-associated DNA Methylation Heterogeneity Contribution (CMHC) score to explore the impact of different immune cell types on heterogeneous CpG site (CpGct) in glioma tissues. We identified eight prognosis-related CpGct to construct a risk score: the Cell-type-associated DNA Methylation Heterogeneity Risk (CMHR) score. CMHR was positively correlated with cytotoxic T-lymphocyte infiltration (CTL), and showed better predictive performance for IDH status (AUC = 0.96) and glioma histological phenotype (AUC = 0.81). Furthermore, DNA methylation alterations of eight CpGct might be related to drug treatments of gliomas. In conclusion, we indicated that DNA methylation heterogeneity is associated with a complex tumour immune microenvironment, glioma phenotype, and patient's prognosis.

Transforming growth factor-β micro-environment mediated immune cell functions in cervical cancer

Propensity to develop cervical cancer (CC) in human papilloma virus (HPV) infected individual could potentially involve the impaired immune functioning. Several stages of HPV surveillance by immune cells in tumor micro-environment (TME) is regulated mainly by transforming growth factor-beta (TGF-β) and is crucial for the establishment of CC. The role of TGF-β in the initiation and progression of CC is very complex and involve different suppressor of mothers against decapentaplegic homolog (SMAD) dependent and SMAD independent signaling mechanism(s). This review summarizes the handling of HPV by immune cells such as T lymphocytes, B lymphocytes, natural killer cells (NK), dendritic cells (DC), monocytes, macrophages, myeloid derived suppressor cells (MDSC) and their regulation by TGF-β. The hijack mechanisms adapted by HPV to evade this surveillance process is discussed. Biomarkers indicating the stages of CC and immune checkpoints that can be targeted for improved outcome are included for immune-based theragnostics. This review also addresses the direct actions of TGF-β on CC cells and tumor/immune cell interactions. Therapies focused on targeting TGF-β using small molecule inhibitors, monoclonal antibodies and TGF-β chimeric antigen receptor (CAR)T cells are collated to understand the current strategies related to TGF-β in the management of CC.

Infiltration of Common Myeloid Progenitor (CMP) Cells is Associated With Less Aggressive Tumor Biology, Lower Risk of Brain Metastasis, Better Response to Immunotherapy, and Higher Patient Survival in Breast Cancer

OBJECTIVE

To investigate the clinical relevance of common myeloid progenitor (CMP) cells in breast tumor microenvironment (TME).

BACKGROUND

The role of rare cells in TME is less studied. In Silico transcriptomic analyses of real-world data enable us to detect and quantify rare cells, including CMP cells.

METHODS

A total of 5176 breast cancer (BC) patients from SCAN-B, METABRIC, and 5 single-cell sequence cohorts were analyzed using the xCell algorithm. The high group was defined as more than two-thirds of the CMP scores in each cohort.

RESULTS

CMP cells consist of 0.07% to 0.25% of bulk breast tumor cells, more in estrogen receptor-positive (ER+) compared with triple-negative (TN) subtype (0.1% to 0.75%, 0.18% to 0.33% of immune cells, respectively). CMP cells did not correlate with any of the myeloid lineages or stem cells in TME. CMP infiltration was higher in smaller tumors, with lower Nottingham grade, and in ER+/HER2- than in TNBC consistently in both SCAN-B and METABRIC cohorts. High CMP was significantly associated with a lower risk of brain metastasis and with better survival, particularly in ER+/HER2-. High CMP enriched epithelial-to-mesenchymal transition and angiogenesis pathways, and less cell proliferation and DNA repair gene sets. High CMP ER+/HER2- was associated with less immune cell infiltration and cytolytic activity ( P <0.001). CMP infiltration correlated with neoadjuvant chemoimmunotherapy response for both ER+/HER2- and TNBC in the ISPY-2 cohort (AUC=0.69 and 0.74, respectively).

CONCLUSIONS

CMP in BC is inversely associated with cell proliferation and brain metastasis, better response to immunotherapy, and survival. This is the first to report the clinical relevance of CMP infiltration in BC.

Machine learning-based autophagy-related prognostic signature for personalized risk stratification and therapeutic approaches in bladder cancer

OBJECTIVE

Bladder cancer (BCa) is a highly lethal urological malignancy characterized by its notable histological heterogeneity. Autophagy has swiftly emerged as a diagnostic and prognostic biomarker in diverse cancer types. Nonetheless, the currently accessible autophagy-related signature specific to BCa remains limited.

METHODS

A refined autophagy-related signature was developed through a 10-fold cross-validation framework, incorporating 101 combinations of machine learning algorithms. The performance of this signature in predicting prognosis and response to immunotherapy was thoroughly evaluated, along with an exploration of potential drug targets and compounds. In vitro and in vivo experiments were conducted to verify the regulatory mechanism of hub gene.

RESULTS

The autophagy-related prognostic signature (ARPS) has exhibited superior performance in predicting the prognosis of BCa compared to the majority of clinical features and other developed markers. Higher ARPS is associated with poorer prognosis and reduced sensitivity to immunotherapy. Four potential targets and five therapeutic agents were screened for patients in the high-ARPS group. In vitro and vivo experiments have confirmed that FKBP9 promotes the proliferation, invasion, and metastasis of BCa.

CONCLUSIONS

Overall, our study developed a valuable tool to optimize risk stratification and decision-making for BCa patients.

Immune microenvironmental heterogeneity according to tumor DNA methylation phenotypes in microsatellite instability-high colorectal cancers

The detailed association between tumor DNA methylation, including CpG island methylation, and tumor immunity is poorly understood. CpG island methylator phenotype (CIMP) is observed typically in sporadic colorectal cancers (CRCs) with microsatellite instability-high (MSI-H). Here, we investigated the differential features of the tumor immune microenvironment according to CIMP status in MSI-H CRCs. CIMP-high (CIMP-H) or CIMP-low/negative (CIMP-L/0) status was determined using MethyLight assay in 133 MSI-H CRCs. All MSI-H CRCs were subjected to digital pathology-based quantification of CD3 + /CD8 + /CD4 + /FoxP3 + /CD68 + /CD204 + /CD177 + tumor-infiltrating immune cells using whole-slide immunohistochemistry. Programmed death-ligand 1 (PD-L1) immunohistochemistry was evaluated using the tumor proportion score (TPS) and combined positive score (CPS). Representative cases were analyzed using whole-exome and RNA-sequencing. In 133 MSI-H CRCs, significantly higher densities of CD8 + tumor-infiltrating lymphocytes (TILs) were observed in CIMP-H tumors compared with CIMP-L/0 tumors. PD-L1 TPS and CPS in CIMP-H tumors were higher than in CIMP-L/0 tumors. Next-generation sequencing revealed that, compared with CIMP-L/0 tumors, CIMP-H tumors had higher fractions of CD8 + T cells/cytotoxic lymphocytes, higher cytolytic activity scores, and activated immune-mediated cell killing pathways. In contrast to CIMP-L/0 tumors, most CIMP-H tumors were identified as consensus molecular subtype 1, an immunogenic transcriptomic subtype of CRC. However, there were no differences in tumor mutational burden (TMB) between CIMP-H and CIMP-L/0 tumors in MSI-H CRCs. In conclusion, CIMP-H is associated with abundant cytotoxic CD8 + TILs and PD-L1 overexpression independent of TMB in MSI-H CRCs, suggesting that CIMP-H tumors represent a typical immune-hot subtype and are optimal candidates for immunotherapy in MSI-H tumors.

Identification of an Amino Acid Metabolism Reprogramming Signature for Predicting Prognosis, Immunotherapy Efficacy, and Drug Candidates in Colon Cancer

Colon cancer ranked third among the most frequently diagnosed cancers worldwide. Amino acid metabolic reprogramming was related to the occurrence and development of colon cancer. We looked for the amino acid metabolism genes (AMGs) associated with amino acid metabolism from molecular signatures database as prognostic markers and constructed amino acid metabolism scoring model (AMS). According to AMS, the patients were divided into high AMS and low AMS groups, and the prognostic characteristics, molecular phenotypes, somatic cell mutation characteristics, immune cell infiltration characteristics, and immunotherapy effect of the two groups were systematically analyzed. Finally, the compounds targeting AMGs were also screened. We screen out 6 prognostic AMGs (P < 0.05) and construct an AMS model based on them. K-M curve indicated that OS in low AMS group was significantly higher than that in high group (P < 0.05), which were validated in multiple datasets. And different AMS groups had different molecular phenotypes, somatic cell mutation characteristics and immune cell infiltration characteristics. Low AMS group had a better effect for immunotherapy. In addition, we predicted potential therapeutic compounds that could bind to AMGs target proteins. AMS model can be used as a hierarchical tool to evaluate the prognosis, immune infiltration characteristics and immunotherapy response ability of colon cancer. And the compounds screened based on AMGs may become new anti-tumor drugs.

Immunohistochemical and transcriptomic characterization of T and myeloid cell infiltrates in canine malignant melanoma

Immune checkpoint inhibitor therapy can provide significant clinical benefit in patients with certain cancer types including melanoma; however, objective responses are only observed for a subset of patients. Mucosal melanoma is a rare melanoma subtype associated with a poor prognosis and, compared with cutaneous melanoma, is significantly less responsive to immune checkpoint inhibitors. Spontaneous canine tumours have emerged as valuable models to inform human cancer studies. In contrast to human melanoma, most canine melanomas are mucosal-an incidence that may be leveraged to better understand the subtype in humans. However, a more comprehensive understanding of the immune landscape of the canine disease is required. Here, we quantify tumour infiltrative T and myeloid cells in canine mucosal (n = 13) and cutaneous (n = 5) melanomas using immunohistochemical analysis of CD3 and MAC387 expression, respectively. Gene expression analysis using the Canine IO NanoString panel was also performed to identify genes and pathways associated with immune cell infiltration. T and myeloid cell densities were variable with geometric means of 158.7 cells/mm2 and 166.7 cells/mm2, respectively. Elevated T cell infiltration was associated with increased expression of cytolytic genes as well as genes encoding the coinhibitory checkpoint molecules PD-1, CTLA-4, TIM-3 and TIGIT; whereas increased myeloid cell infiltration was associated with elevated expression of protumourigenic cytokines. These data provide a basic characterization of the tumour microenvironment of canine malignant melanoma and suggest that, like human melanoma, inherent variability in anti-tumour T cell responses exists and that a subset of canine melanomas may respond better to immunomodulation.

Inferring Characteristics of the Tumor Immune Microenvironment of Patients with HNSCC from Single-Cell Transcriptomics of Peripheral Blood

In this study, we explore the possibility of inferring characteristics of the tumor immune microenvironment from the blood. Specifically, we investigate two datasets of patients with head and neck squamous cell carcinoma with matched single-cell RNA sequencing (scRNA-seq) from peripheral blood mononuclear cells (PBMCs) and tumor tissues. Our analysis shows that the immune cell fractions and gene expression profiles of various immune cells within the tumor microenvironment can be inferred from the matched PBMC scRNA-seq data. We find that the established exhausted T-cell signature can be predicted from the blood and serve as a valuable prognostic blood biomarker of immunotherapy response. Additionally, our study reveals that the inferred ratio between tumor memory B- and regulatory T-cell fractions is predictive of immunotherapy response and is superior to the well-established cytolytic and exhausted T-cell signatures. These results highlight the promising potential of PBMC scRNA-seq in cancer immunotherapy and warrant, and will hopefully facilitate, further investigations on a larger scale. The code for predicting tumor immune microenvironment from PBMC scRNA-seq, TIMEP, is provided, offering other researchers the opportunity to investigate its prospective applications in various other indications.

SIGNIFICANCE

Our work offers a new and promising paradigm in liquid biopsies to unlock the power of blood single-cell transcriptomics in cancer immunotherapy.

Engineering immune-evasive allogeneic cellular immunotherapies

Allogeneic cellular immunotherapies hold a great promise for cancer treatment owing to their potential cost-effectiveness, scalability and on-demand availability. However, immune rejection of adoptively transferred allogeneic T and natural killer (NK) cells is a substantial obstacle to achieving clinical responses that are comparable to responses obtained with current autologous chimeric antigen receptor T cell therapies. In this Perspective, we discuss strategies to confer cell-intrinsic, immune-evasive properties to allogeneic T cells and NK cells in order to prevent or delay their immune rejection, thereby widening the therapeutic window. We discuss how common viral and cancer immune escape mechanisms can serve as a blueprint for improving the persistence of off-the-shelf allogeneic cell therapies. The prospects of harnessing genome editing and synthetic biology to design cell-based precision immunotherapies extend beyond programming target specificities and require careful consideration of innate and adaptive responses in the recipient that may curtail the biodistribution, in vivo expansion and persistence of cellular therapeutics.

MEST promotes immune escape in gastric cancer by downregulating MHCI expression via SHP2

BACKGROUND

Immune escape is a major obstacle to T-cell-based immunotherapy for cancers such as gastric cancer (GC). Mesoderm-specific transcript (MEST) is a tumor-promoting factor that regulates multiple oncogenic signaling pathways. However, the role of MEST-mediated immune escape is unclear.

METHODS

Bioinformatics analysis of MEST expression and enrichment pathways were performed Quantitative reverse transcription PCR (qPCR) or western blot was used to detect the expression of MEST, Src homology region 2-containing protein tyrosine phosphatase 2 (SHP2), Major histocompatibility class I (MHCI)-related genes. Cell function was assessed by Cell Counting Kit (CCK)-8, Transwell, Lactate dehydrogenase (LDH) kit, flow cytometry, enzyme-linked immunosorbent assay (ELISA), and immunohistochemistry (IHC). Xenograft nude mice and immune-reconstructed mice were used to test the effects of different treatments on tumor growth and immune escape in vivo.

RESULTS

MEST was upregulated in GC and promoted tumor proliferation, migration, and invasion. Rescue experiments revealed that TNO155 treatment or knockdown of SHP2 promoted the killing ability of CD8+ T cells and the expression of granzyme B (GZMB) and interferon-gamma (IFN-γ), and MEST overexpression reversed the effect. In vivo experiments confirmed that MEST promoted tumor growth, knockdown of MEST inhibited immune escape in GC, and that combination treatment with anti-PD-1 improved anti-tumor activity.

CONCLUSION

In this study, we demonstrated that MEST inhibited IFN-γ secretion from CD8+ T cells by up-regulating SHP2, thereby downregulating MHCI expression in GC cells to promote immune escape and providing a new T cell-based therapeutic potential for GC.

Impact of clonal TP53 mutations with loss of heterozygosity on adjuvant chemotherapy and immunotherapy in gastric cancer

BACKGROUND

This study aimed to reveal the effect of TP53 status on clinical outcomes and underlying mechanism in gastric cancer (GC) patients.

METHODS

TP53 status was divided into three groups according to genome sequencing, namely clonal mutations with LOH (C-LOH), clonal diploid or subclonal mutations (CD-SC), and wild type (WT). The p53 protein activity was divided into over-expression (OE), Null and WT according to immunohistochemical staining. Four cohorts, including the TCGA, SMC, ZSHS and FUSCC cohort, were analyzed for association between TP53 mutation status and clinical outcomes and the underlying mechanism.

RESULTS

In TCGA cohort, TP53 CD-SC were associated with superior overall survival compared to TP53 C-LOH cases. GC patients could benefit from ACT only in TP53 CD-SC/ p53 OE and TP53/ p53 WT subgroups, and TP53 C-LOH subgroup demonstrated the worst response to pembrolizumab among three subgroups. Genomic and immunophenotypic deconvolution revealed that TP53 C-LOH, CD-SC and WT differed for genomic and immune-related features.

CONCLUSIONS

TP53 C-LOH GCs with genomic instability and immune evasion phenotype have poor clinical outcomes in patients treated with ACT or immunotherapy.

Altered epitopes enhance macrophage-mediated anti-tumour immunity to low-immunogenic tumour mutations

Personalized neoantigen therapy has shown long-term and stable efficacy in specific patient populations. However, not all patients have sufficient levels of neoantigens for treatment. Although somatic mutations are commonly found in tumours, a significant portion of these mutations do not trigger an immune response. Patients with low mutation burdens continue to exhibit unresponsiveness to this treatment. We propose a design paradigm for neoantigen vaccines by utilizing the highly immunogenic unnatural amino acid p-nitrophenylalanine (pNO2Phe) for sequence alteration of somatic mutations that failed to generate neoepitopes. This enhances the immunogenicity of the mutations and transforms it into a suitable candidate for immunotherapy. The nitrated altered epitope vaccines designed according to this paradigm is capable of activating circulating CD8+ T cells and inducing immune cross-reactivity against autologous mutated epitopes in different MHC backgrounds (H-2Kb, H-2Kd, and human HLA-A02:01), leading to the elimination of tumour cells carrying the mutation. After immunization with the altered epitopes, tumour growth was significantly inhibited. It is noteworthy that nitrated epitopes induce tumour-infiltrating macrophages to differentiate into the M1 phenotype, surprisingly enhancing the MHC II molecule presenting pathway of macrophages. Nitrated epitope-treated macrophages have the potential to cross-activate CD4+ and CD8+ T cells, which may explain why pNO2Phe can enhance the immunogenicity of epitopes. Meanwhile, the immunosuppressive microenvironment of the tumour is altered due to the activation of macrophages. The nitrated neoantigen vaccine strategy enables the design of vaccines targeting non-immunogenic tumour mutations, expanding the pool of potential peptides for personalized and shared novel antigen therapy. This approach provides treatment opportunities for patients previously ineligible for new antigen vaccine therapy.

Clinical Progresses and Challenges of Bispecific Antibodies for the Treatment of Solid Tumors

In recent years, bispecific antibodies (BsAbs) have emerged as a promising therapeutic strategy against tumors. BsAbs can recruit and activate immune cells, block multiple signaling pathways, and deliver therapeutic payloads directly to tumor sites. This review provides a comprehensive overview of the recent advances in the development and clinical application of BsAbs for the treatment of solid tumors. We discuss the different formats, the unique mechanisms of action, and the clinical outcomes of the most advanced BsAbs in solid tumor therapy. Several studies have also analyzed the clinical progress of bispecific antibodies. However, this review distinguishes itself by exploring the challenges associated with bispecific antibodies and proposing potential solutions. As the field progresses, BsAbs hold promise to redefine cancer treatment paradigms and offer new hope to patients with solid tumors.

Multiomics and machine learning-based analysis of pancancer pseudouridine modifications

Pseudouridine widely affects the stability and function of RNA. However, our knowledge of pseudouridine properties in tumors is incomplete. We systematically analyzed pseudouridine synthases (PUSs) expression, genomic aberrations, and prognostic features in 10907 samples from 33 tumors. We found that the pseudouridine-associated pathway was abnormal in tumors and affected patient prognosis. Dysregulation of the PUSs expression pattern may arise from copy number variation (CNV) mutations and aberrant DNA methylation. Functional enrichment analyses determined that the PUSs expression was closely associated with the MYC, E2F, and MTORC1 signaling pathways. In addition, PUSs are involved in the remodeling of the tumor microenvironment (TME) in solid tumors, such as kidney and lung cancers. Particularly in lung cancer, increased expression of PUSs is accompanied by increased immune checkpoint expression and Treg infiltration. The best signature model based on more than 112 machine learning combinations had good prognostic ability in ACC, DLBC, GBM, KICH, MESO, THYM, TGCT, and PRAD tumors, and is expected to guide immunotherapy for 19 tumor types. The model was also effective in identifying patients with tumors amenable to etoposide, camptothecin, cisplatin, or bexarotene treatment. In conclusion, our work highlights the dysregulated features of PUSs and their role in the TME and patient prognosis, providing an initial molecular basis for future exploration of pseudouridine. Studies targeting pseudouridine are expected to lead to the development of potential diagnostic strategies and the evaluation and improvement of antitumor therapies.

Multimodal analysis unveils tumor microenvironment heterogeneity linked to immune activity and evasion

The cellular and molecular heterogeneity of tumors is a major obstacle to cancer immunotherapy. Here, we use a systems biology approach to derive a signature of the main sources of heterogeneity in the tumor microenvironment (TME) from lung cancer transcriptomics. We demonstrate that this signature, which we called iHet, is conserved in different cancers and associated with antitumor immunity. Through analysis of single-cell and spatial transcriptomics data, we trace back the cellular origin of the variability explaining the iHet signature. Finally, we demonstrate that iHet has predictive value for cancer immunotherapy, which can be further improved by disentangling three major determinants of anticancer immune responses: activity of immune cells, immune infiltration or exclusion, and cancer-cell foreignness. This work shows how transcriptomics data can be integrated to derive a holistic representation of the phenotypic heterogeneity of the TME and to predict its unfolding and fate during immunotherapy with immune checkpoint blockers.

Prognostic value of four immune-related genes in lower-grade gliomas: a biomarker discovery study

Introduction

The tumor microenvironment and IRGs are highly correlated with tumor occurrence, progression, and prognosis. However, their roles in grade II and III gliomas, termed LGGs in this study, remain to be fully elucidated. Our research aims to develop immune-related features for risk stratification and prognosis prediction in LGG.

Methods

Using the ssGSEA method, we assessed the immune characteristics of the LGG population. We conducted differential analysis using LGG samples from the TCGA database and normal samples from GTEx, identifying 412 differentially expressed immune-related genes (DEIRGs). Subsequently, we utilized univariate Cox, LASSO, and multivariate Cox regression analyses to establish both a gene predictive model and a nomogram predictive model.

Results

Here, we found that the ESTIMATE score, immune score and stromal score of high-immunity, high-grade and isocitrate dehydrogenase (IDH) wild-type glioma were higher than those of the corresponding group, and the tumor purity was lower. Higher ESTIMATE scores, stromal scores and immune scores indicated a poor prognosis in patients with LGG. Our four-gene prognostic model demonstrated superior accuracy compared to other molecular features. Validation using the CGGA as a testing set and the combined TCGA and CGGA cohort confirmed its robust prognostic value. Additionally, a nomogram integrating the prognostic model and clinical variables showed enhanced predictive capability.

Discussion

Our study highlights the prognostic significance of the identified four DEIRGs (KLRC3, MR1, PDIA2, and RFXAP) in LGG patients. The predictive model and nomogram developed herein offer valuable tools for personalized treatment strategies in LGG. Future research should focus on further validating these findings and exploring the functional roles of these DEIRGs within the LGG tumor microenvironment.

Unveiling major histocompatibility complex-mediated pan-cancer immune features by integrated single-cell and bulk RNA sequencing

Immune checkpoint inhibitors (ICIs) have transformed cancer therapy, yet persistent challenges such as low response rate and significant heterogeneity necessitate attention. The pivotal role of the major histocompatibility complex (MHC) in ICI efficacy, its intricate impacts and potentials as a prognostic marker, warrants comprehensive exploration. This study integrates single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, and spatial transcriptomic analyses to unveil pan-cancer immune characteristics governed by the MHC transcriptional feature (MHC.sig). Developed through scRNA-seq analysis of 663,760 cells across diverse cohorts and validated in 30 solid cancer types, the MHC.sig demonstrates a robust correlation between immune-related genes and infiltrating immune cells, highlighting its potential as a universal pan-cancer marker for anti-tumor immunity. Screening the MHC.sig for therapeutic targets using CRISPR data identifies potential genes for immune therapy synergy and validates its predictive efficacy for ICIs responsiveness across diverse datasets and cancer types. Finally, analysis of cellular communication patterns reveals interactions between C1QC+macrophages and malignant cells, providing insights into potential therapeutic agents and their sensitivity characteristics. This comprehensive analysis positions the MHC.sig as a promising marker for predicting immune therapy outcomes and guiding combinatorial therapeutic strategies.

Case report: Immune response characterization of a pseudoprogression in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic NSCLC

A patient with a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated metastatic non-small cell lung cancer (NSCLC) experienced a multisite radiological progression at 3 months after initiation of chemoimmunotherapy as first-line treatment for metastatic disease. After the radiological progression, while she was not undergoing treatment, the patient had spontaneous lesions shrinkage and further achieved a prolonged complete response. Genomic and transcriptomic data collected at baseline and at the time of pseudoprogression allowed us to biologically characterize this rare response pattern. We observed the presence of a tumor-specific T-cell response against tumor-specific neoantigens (TNAs). Endogenous retroviruses (ERVs) expression following chemoimmunotherapy was also observed, concurrent with biological features of an anti-viral-like innate immune response with type I IFN signaling and production of CXCR3-associated chemokines. This is the first biological characterization of a NSCLC pseudoprogression under chemoimmunotherapy followed by a prolonged complete response in a PD-L1-negative, TMB-low, KEAP1/STK11 co-mutated NSCLC. These clinical and biological data underline that even patients with multiple factors of resistance to immune checkpoint inhibitors could trigger a tumor-specific immune response to tumor neoantigen, leading to complete eradication of the tumor and probably a vaccinal immune response.

Single-Cell Analysis Provides New Insights into the Roles of Tertiary Lymphoid Structures and Immune Cell Infiltration in Kidney Injury and Chronic Kidney Disease

Chronic kidney disease (CKD) is a global health concern with high morbidity and mortality. Acute kidney injury (AKI) is a pivotal risk factor for the progression of CKD, and the rate of AKI-to-CKD progression increases with aging. Intrarenal inflammation is a fundamental mechanism underlying AKI-to-CKD progression. Tertiary lymphoid structures (TLSs), ectopic lymphoid aggregates formed in nonlymphoid organs, develop in aged injured kidneys, but not in young kidneys, with prolonged inflammation and maladaptive repair, which potentially exacerbates AKI-to-CKD progression in aged individuals. Dysregulated immune responses are involved in the pathogenesis of various kidney diseases, such as IgA nephropathy, lupus nephritis, and diabetic kidney diseases, thereby deteriorating kidney function. TLSs also develop in several kidney diseases, including transplanted kidneys and renal cell carcinoma. However, the precise immunologic mechanisms driving AKI-to-CKD progression and development of these kidney diseases remain unclear, which hinders the development of novel therapeutic approaches. This review aims to describe recent findings from single-cell analysis of cellular heterogeneity and complex interactions among immune and renal parenchymal cells, which potentially contribute to the pathogenesis of AKI-to-CKD progression and other kidney diseases, highlighting the mechanisms of formation and pathogenic roles of TLSs in aged injured kidneys.

Immune-related gene signature improves prognosis prediction in patients with breast cancer and associates it with tumor immunity and inflammatory response

BACKGROUND

The prognostic potential of immune-related genes, particularly immune checkpoint inhibitors (ICIs) and long non-coding RNAs (lncRNAs), is gaining attention for evaluating the prognosis of breast cancer patients.

METHODS

We analyzed 23 datasets to identify 15 ICI-related mRNAs and 5 immune-related lncRNAs, creating a robust immune score (IS). This score was used to classify patients into high and low IS groups and assess their survival outcomes.

RESULTS

Patients with high IS showed significantly poorer overall survival (OS) and progression-free survival (PFS) compared to those with low IS. Multivariate Cox regression analysis confirmed IS as an independent prognostic factor. Additionally, high IS was associated with higher mutation loads and neoantigen profiles, while low IS correlated with enhanced immune cell infiltration.

CONCLUSIONS

The immune score developed from ICI-related mRNAs and lncRNAs effectively predicts the prognosis of breast cancer patients and highlights the differential immune and inflammatory responses between patients with varying levels of immune score. This underscores the relevance of IS in guiding therapeutic decisions and tailoring patient management strategies in clinical settings.

RAD51 High-Expressed Hepatocellular Carcinomas are Associated With High Cell Proliferation

INTRODUCTION

RAD51 is a pivotal DNA repair gene managing double-stranded DNA break recognition and repair. RAD51 high expression was associated with adverse outcomes in other cancer types. This study aims to investigate the tumor microenvironment and immune landscape in the RAD51 high-expressed Hepatocellular Carcinoma (HCCs).

METHODS

A total of 467 patients from two large independent cohorts with clinical and transcriptomic data were obtained. The cohort was dichotomized based on the median RAD51 gene expression. xCell and Gene Set Enrichment Analysis (GSEA) were used.

RESULTS

RAD51 high-expressed HCCs were associated with worse recurrence-free, progression-free, disease-specific, and overall survival (all P < 0.05). While RAD51 high-expressed HCCs were associated with intratumoral heterogeneity, homologous recombination deficiency, and fraction altered scores, mutation or neoantigens were not increased in this group. xCell analysis demonstrated inconsistent immune cell infiltration between two cohorts. Cytolytic activity as well as GSEA with immune-related gene sets also demonstrated inconsistent results between two cohorts as well. On the other hand, RAD51 expression was significantly increased in higher-grade tumors, larger tumors, and higher clinical stages. RAD51 high-expressed HCCs were found to have elevated proliferation score. Furthermore, GSEA exhibited significant enrichment of all the cell proliferation-related gene sets in the Hallmark collection, including E2F targets, G2M checkpoint, Mitotic spindle, MYC targets, and MTORC1 signaling consistently in both cohorts (all false discovery rate < 0.25).

CONCLUSIONS

RAD51 high-expressed HCCs were associated with worse survival and with increased cell proliferation and were not necessarily associated with immune infiltration or inflammation.

Detecting HLA loss of heterozygosity within a standard diagnostic sequencing workflow for prognostic and therapeutic opportunities

To enable interrogation of tumor HLA LOH as a clinical diagnostic for precision oncology, we developed and validated an assay that detects HLA LOH within the context of an FDA-approved clinical diagnostic test, Tempus xT CDx. Validation was conducted via: (1) analytical evaluation of 17 archival patient samples and 42 cell line admixtures and (2) independent clinical evaluation of LOH prevalence in the HLA-A gene (HLA-A LOH) across 10,982 patients. To evaluate the prognostic relevance of HLA-A LOH we assessed 256 immunotherapy-treated non-small cell lung cancer (NSCLC) patients. To determine the feasibility of prospectively identifying and enrolling HLA-A LOH patients into a clinical trial, we established BASECAMP-1 (NCT04981119). We observed a positive predictive agreement of 97% and a negative predictive agreement of 100% in samples with ≥ 40% tumor purity. We observed HLA-A LOH in 16.1% of patients (1771/10,982), comparable to previous reports. HLA-A LOH was associated with longer survival among NSCLC adenocarcinoma patients (HR = 0.60, 95% CI [0.37, 0.96], p = 0.032) with a trend towards shorter survival among squamous cell patients (HR = 1.64, 95% CI [0.80, 3.41], p = 0.183). In 20 months, we prospectively screened 1720 subjects using the Tempus AWARE program, identifying 26 HLA-A*02 LOH patients at 8 sites, with 14 (54%) enrolled into BASECAMP-1. In conclusion, we developed and validated an investigational assay that detects tumor HLA LOH within an FDA-approved clinical diagnostic test, enabling HLA LOH utilization in diagnostic, prognostic, and therapeutic applications.

Identification of pyroptosis subtypes and prognosis model of hepatocellular carcinoma based on pyroptosis-related genes

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor with poor prognosis. Pyroptosis, a type of programmed cell death, regulates tumor cell development. However, the role of pyroptosis-related genes (PRGs) in HCC and their association with prognosis are unclear.

METHODS

We conducted bioinformatics analysis to identify PRGs in The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC) patients. Consensus clustering classified patients into different subtypes. We used LASSO regression to established a pyroptosis subtype-related score (PSRS) related to prognosis. OncoPredict identified potential pharmaceuticals based on PSRS.

RESULTS

We found 20 HCC-related PRGs in 335 TCGA-LIHC patients. Consensus clustering classified patients into two subtypes. Subtype I had better overall survival and higher response to anti-PD1 treatment. The prognostic model involving 20 genes predicted poorer prognosis for high-PSRS group. The model was validated in two external cohorts. OncoPredict identified 65 potential pharmaceuticals based on PSRS.

CONCLUSION

Our investigation revealed a correlation between pyroptosis and HCC. We established PSRS as independent risk factors for predicting prognosis. The study paves the way for using PRGs as prognostic biomarkers and exploring personalized therapy for HCC.

Prognostic and therapeutic potential of imbalance between PD-1+CD8 and ICOS+Treg cells in advanced HBV-HCC

Over 50% of patients with hepatitis B virus-associated hepatocellular carcinoma (HBV-HCC) are diagnosed at an advanced stage, which is characterized by immune imbalance between CD8+ T cells and regulatory T (Treg) cells that accelerates disease progression. However, there is no imbalance indicator to predict clinical outcomes. Here, we show that the proportion of CD8+ T cells decreases and Treg cells increases in advanced HBV-HCC patients. During this stage, CD8+ T cells and Treg cells expressed the coinhibitory molecule PD-1 and the costimulatory molecule ICOS, respectively. Additionally, the ratio between PD-1+CD8 and ICOS+Tregs showed significant changes. Patients were further divided into high- and low-ratio groups: PD-1+CD8 and ICOS+Tregs high- (PD-1/ICOShi) and low-ratio (PD-1/ICOSlo) groups according to ratio median. Compared with PD-1/ICOSlo patients, the PD-1/ICOShi group had better clinical prognosis and weaker CD8+ T cells exhaustion, and the T cell-killing and proliferation functions were more conservative. Surprisingly, the small sample analysis found that PD-1/ICOShi patients exhibited a higher proportion of tissue-resident memory T (TRM) cells and had more stable killing capacity and lower apoptosis capacity than PD-1/ICOSlo advanced HBV-HCC patients treated with immune checkpoint inhibitors (ICIs). In conclusion, the ratio between PD-1+CD8 and ICOS+Tregs was associated with extreme immune imbalance and poor prognosis in advanced HBV-HCC. These findings provide significant clinical implications for the prognosis of advanced HBV-HCC and may serve as a theoretical basis for identifying new targets in immunotherapy.

3D bioprinted tumor model: a prompt and convenient platform for overcoming immunotherapy resistance by recapitulating the tumor microenvironment

BACKGROUND

Cancer immunotherapy is receiving worldwide attention for its induction of an anti-tumor response. However, it has had limited efficacy in some patients who acquired resistance. The dynamic and sophisticated complexity of the tumor microenvironment (TME) is the leading contributor to this clinical dilemma. Through recapitulating the physiological features of the TME, 3D bioprinting is a promising research tool for cancer immunotherapy, which preserves in vivo malignant aggressiveness, heterogeneity, and the cell-cell/matrix interactions. It has been reported that application of 3D bioprinting holds potential to address the challenges of immunotherapy resistance and facilitate personalized medication.

CONCLUSIONS AND PERSPECTIVES

In this review, we briefly summarize the contributions of cellular and noncellular components of the TME in the development of immunotherapy resistance, and introduce recent advances in 3D bioprinted tumor models that served as platforms to study the interactions between tumor cells and the TME. By constructing multicellular 3D bioprinted tumor models, cellular and noncellular crosstalk is reproduced between tumor cells, immune cells, fibroblasts, adipocytes, and the extracellular matrix (ECM) within the TME. In the future, by quickly preparing 3D bioprinted tumor models with patient-derived components, information on tumor immunotherapy resistance can be obtained timely for clinical reference. The combined application with tumoroid or other 3D culture technologies will also help to better simulate the complexity and dynamics of tumor microenvironment in vitro. We aim to provide new perspectives for overcoming cancer immunotherapy resistance and inspire multidisciplinary research to improve the clinical application of 3D bioprinting technology.

Loss of STK11 Suppresses Lipid Metabolism and Attenuates KRAS-Induced Immunogenicity in Patients with Non-Small Cell Lung Cancer

As many as 30% of the patients with non-small cell lung cancer harbor oncogenic KRAS mutations, which leads to extensive remodeling of the tumor immune microenvironment. Although co-mutations in several genes have prognostic relevance in KRAS-mutated patients, their effect on tumor immunogenicity are poorly understood. In the present study, a total of 189 patients with non-small cell lung cancer underwent a standardized analysis including IHC, whole-exome DNA sequencing, and whole-transcriptome RNA sequencing. Patients with activating KRAS mutations demonstrated a significant increase in PDL1 expression and CD8+ T-cell infiltration. Both were increased in the presence of a co-occurring TP53 mutation and lost with STK11 co-mutation. Subsequent genomic analysis demonstrated that KRAS/TP53 co-mutated tumors had a significant decrease in the expression of glycolysis-associated genes and an increase in several genes involved in lipid metabolism, notably lipoprotein lipase, low-density lipoprotein receptor, and LDLRAD4. Conversely, in the immune-excluded KRAS/STK11 co-mutated group, we observed diminished lipid metabolism and no change in anaerobic glycolysis. Interestingly, in patients with low expression of lipoprotein lipase, low-density lipoprotein receptor, or LDLRAD4, KRAS mutations had no effect on tumor immunogenicity. However, in patients with robust expression of these genes, KRAS mutations were associated with increased immunogenicity and associated with improved overall survival. Our data further suggest that the loss of STK11 may function as a metabolic switch, suppressing lipid metabolism in favor of glycolysis, thereby negating KRAS-induced immunogenicity. Hence, this concept warrants continued exploration, both as a predictive biomarker and potential target for therapy in patients receiving ICI-based immunotherapy.

SIGNIFICANCE

In patients with lung cancer, we demonstrate that KRAS mutations increase tumor immunogenicity; however, KRAS/STK11 co-mutated patients display an immune-excluded phenotype. KRAS/STK11 co-mutated patients also demonstrated significant downregulation of several key lipid metabolism genes, many of which were associated with increased immunogenicity and improved overall survival in KRAS-mutated patients. Hence, alteration to lipid metabolism warrants further study as a potential biomarker and target for therapy in patients with KRAS-mutated lung cancer.

Antitumor immunity and prognosis value elicited by FAT3 and LRP1B co-mutation in endometrial cancer

OBJECTIVE

FAT3 and LRP1B are two tumor suppressor genes with high mutation frequency in multiple cancer types, we sought to investigate the prognostic and immunological significance of these two genes in EC.

METHODS

Based on a cohort of 502 EC samples, we conducted a comprehensive analysis of its multidimensional data types including genomic, transcriptomic, and clinical information, the potential impact of FAT3 and LRP1B co-mutation on antitumor immune response and prognosis were systematically discussed.

RESULTS

We observed that FAT3 and LRP1B co-mutation was not only defined a dataset with prominently increased TMB, decreased tumor aneuploidy, and specially enriched in MSI-H subtype, but also manifested increased expression of immune-related markers, especially exclusive upregulation of PD-L1 levels and higher PD-L1+/CD8A+ proportion. Further analysis focused on lymphocyte infiltration and pathway enrichment explored the immune cell composition of the microenvironment and underlying molecular mechanisms affecting tumor development. Furthermore, EC patients with FAT3 and LRP1B co-mutation possessed significantly prolonged PFS and OS, and the co-mutation status was proved to be an independent prognostic factor. And a nomogram with high predictive performance was constructed by incorporating co-mutation with clinical features. More strikingly, the prognosis of MSI-H patients in EC with co-mutation was significantly improved, and their survival reached a level consistent with the POLE subtype.

CONCLUSIONS

In endometrial cancer, co-mutation of FAT3 and LRP1B not only leads to activation of the immune state, but also represents a subgroup with an improved prognosis, particularly in the MSI-H subtype.

Identification and validation of tryptophan-related gene signatures to predict prognosis and immunotherapy response in lung adenocarcinoma reveals a critical role for PTTG1

Introduction

Tryptophan metabolism is strongly associated with immunosuppression and may influence lung adenocarcinoma prognosis as well as tumor microenvironment alterations.

Methods

Sequencing datasets were obtained from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database. Two different clusters were identified by consensus clustering, and prognostic models were established based on differentially expressed genes (DEGs) in the two clusters. We investigated differences in mutational landscapes, enrichment pathways, immune cell infiltration, and immunotherapy between high- and low-risk scoring groups. Single-cell sequencing data from Bischoff et al. were used to identify and quantify tryptophan metabolism, and model genes were comprehensively analyzed. Finally, PTTG1 was analyzed at the pan-cancer level by the pan-TCGA cohort.

Results

Risk score was defined as an independent prognostic factor for lung adenocarcinoma and was effective in predicting immunotherapy response in patients with lung adenocarcinoma. PTTG1 is one of the key genes, and knockdown of PTTG1 in vitro decreases lung adenocarcinoma cell proliferation and migration and promotes apoptosis and down-regulation of tryptophan metabolism regulators in lung adenocarcinoma cells.

Discussion

Our study revealed the pattern and molecular features of tryptophan metabolism in lung adenocarcinoma patients, established a model of tryptophan metabolism-associated lung adenocarcinoma prognosis, and explored the roles of PTTG1 in lung adenocarcinoma progression, EMT process, and tryptophan metabolism.

Genomics and proteomics to determine novel molecular subtypes and predict the response to immunotherapy and the effect of bevacizumab in glioblastoma

Glioblastoma (GBM) is a highly aggressive, infiltrative malignancy that cannot be completely cured by current treatment modalities, and therefore requires more precise molecular subtype signatures to predict treatment response for personalized precision therapy. Expression subtypes of GBM samples from the Cancer Genome Atlas (TCGA) were identified using BayesNM and compared with existing molecular subtypes of GBM. Biological features of the subtypes were determined by single-sample gene set enrichment analysis. Genomic and proteomic data from GBM samples were combined and Genomic Identification of Significant Targets in Cancer analysis was used to screen genes with recurrent somatic copy-number alterations phenomenon. The immune environment among subtypes was compared by assessing the expression of immune molecules and the infiltration of immune cells. Molecular subtypes adapted to immunotherapy were identified based on Tumor Immune Dysfunction and Exclusion (TIDE) score. Finally, least absolute shrinkage and selection operator (LASSO) logistic regression was performed on the expression profiles of S2, S3 and S4 in TCGA-GBM and RPPA to determine the respective corresponding best predictive model. Four novel molecular subtypes were classified. Specifically, S1 exhibited a low proliferative profile; S2 exhibited the profile of high proliferation, IDH1 mutation, TP53 mutation and deletion; S3 was characterized by high immune scores, innate immunity and adaptive immune infiltration scores, with the lowest TIDE score and was most likely to benefit from immunotherapy; S4 was characterized by high proliferation, EGFR amplification, and high protein abundance, and was the most suitable subtype for bevacizumab. LASSO analysis constructed the best prediction model composed of 13 genes in S2 with an accuracy of 96.7%, and the prediction model consisting of 17 genes in S3 with an accuracy of 86.7%, and screened 14 genes as components of the best prediction model in S4 with an accuracy of 93%. To conclude, our study classified reproducible and robust molecular subtypes of GBM, and these findings might contribute to the identification of patients responding to immunotherapy, thereby improving GBM prognosis.

Dual blockade immunotherapy targeting PD-1/PD-L1 and CTLA-4 in lung cancer

Cancer immunotherapies, represented by immune checkpoint inhibitors (ICIs), have reshaped the treatment paradigm for both advanced non-small cell lung cancer and small cell lung cancer. Programmed death receptor-1/programmed death receptor ligand-1 (PD-1/PD-L1) and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) are some of the most common and promising targets in ICIs. Compared to ICI monotherapy, which occasionally demonstrates treatment resistance and limited efficacy, the dual blockade immunotherapy targeting PD-1/PD-L1 and CTLA-4 operates at different stages of T cell activation with synergistically enhancing immune responses against cancer cells. This emerging dual therapy heralds a new direction for cancer immunotherapy, which, however, may increase the risk of drug-related adverse reactions while improving efficacy. Previous clinical trials have explored combination therapy strategy of anti-PD-1/PD-L1 and anti-CTLA-4 agents in lung cancer, yet its efficacy remains to be unclear with the inevitable incidence of immune-related adverse events. The recent advent of bispecific antibodies has made this sort of dual targeting more feasible, aiming to alleviate toxicity without compromising efficacy. Thus, this review highlights the role of dual blockade immunotherapy targeting PD-1/PD-L1 and CTLA-4 in treating lung cancer, and further elucidates its pre-clinical mechanisms and current advancements in clinical trials. Besides, we also provide novel insights into the potential combinations of dual blockade therapies with other strategies to optimize the future treatment mode for lung cancer.

TG6050, an oncolytic vaccinia virus encoding interleukin-12 and anti-CTLA-4 antibody, favors tumor regression via profound immune remodeling of the tumor microenvironment

BACKGROUND

TG6050 was designed as an improved oncolytic vector, combining the intrinsic properties of vaccinia virus to selectively replicate in tumors with the tumor-restricted expression of recombinant immune effectors to modify the tumor immune phenotype. These properties might be of particular interest for "cold" tumors, either poorly infiltrated or infiltrated with anergic T cells.

METHODS

 TG6050, an oncolytic vaccinia virus encodes single-chain human interleukin-12 (hIL-12) and full-length anti-cytotoxic T-lymphocyte-associated antigen-4 (@CTLA-4) monoclonal antibody. The relevant properties of TG6050 (replication, cytopathy, transgenes expression and functionality) were extensively characterized in vitro. The biodistribution and pharmacokinetics of the viral vector, @CTLA-4 and IL-12, as well as antitumoral activities (alone or combined with immune checkpoint inhibitors) were investigated in several "hot" (highly infiltrated) and "cold" (poorly infiltrated) syngeneic murine tumor models. The mechanism of action was deciphered by monitoring both systemic and intratumoral immune responses, and by tumor transcriptome analysis. The safety of TG6050 after repeated intravenous administrations was evaluated in cynomolgus monkeys, with a focus on the level of circulating IL-12.

RESULTS

Multiplication and propagation of TG6050 in tumor cells in vitro and in vivo were associated with local expression of functional IL-12 and @CTLA-4. This dual mechanism translated into a strong antitumoral activity in both "cold" and "hot" tumor models (B16F10, LLC1 or EMT6, CT26, respectively) that was further amplified when combined with anti-programmed cell death protein-1. Analysis of changes in the tumor microenvironment (TME) after treatment with TG6050 showed increases in interferon-gamma, of CD8+T cells, and of M1/M2 macrophages ratio, as well as a drastic decrease of regulatory T cells. These local modifications were observed alongside bolstering a systemic and specific antitumor adaptive immune response. In toxicology studies, TG6050 did not display any observable adverse effects in cynomolgus monkeys.

CONCLUSIONS

TG6050 effectively delivers functional IL-12 and @CTLA-4 into the tumor, resulting in strong antitumor activity. The shift towards an inflamed TME correlated with a boost in systemic antitumor T cells. The solid preclinical data and favorable benefit/risk ratio paved the way for the clinical evaluation of TG6050 in metastatic non-small cell lung cancer (NCT05788926 trial in progress).

Effect of neoadjuvant chemoradiotherapy with or without PD-1 antibody sintilimab in pMMR locally advanced rectal cancer: A randomized clinical trial

Neoadjuvant chemoradiotherapy (NACRT) was the standard treatment for patients with locally advanced rectal cancer (LARC) with proficient mismatch repair (pMMR) proteins. In this randomized phase 2 trial (ClinicalTrial.gov: NCT04304209), 134 pMMR LARC patients were randomly (1:1) assigned to receive NACRT or NACRT and the programmed cell death protein 1 (PD-1) antibody sintilimab. As the primary endpoint, the total complete response (CR) rate is 26.9% (18/67, 95% confidence interval [CI] 16.0%-37.8%) and 44.8% (30/67, 95% CI 32.6%-57.0%) in the control and experimental arm, respectively, with significant difference (p = 0.031 for chi-squared test). Response ratio is 1.667 (95% CI 1.035-2.683). Immunohistochemistry shows PD-1 ligand 1 (PD-L1) combined positive score is associated with the synergistic effect. The safety profile is similar between the arms. Adding the PD-1 antibody sintilimab to NACRT significantly increases the CR rate in pMMR LARC, with a manageable safety profile. PD-L1 positivity may help identify patients who might benefit most from the combination therapy.

IRF8 deficiency-induced myeloid-derived suppressor cell promote immune evasion in lung adenocarcinoma

BACKGROUND

Patients with lung adenocarcinoma (LUAD) have a low response rate to immune checkpoint blockade. It is highly important to explore the tumor immune escape mechanism of LUAD patients and expand the population of patients who may benefit from immunotherapy.

METHODS

Based on 954 bulk RNA-seq data of LUAD patients and 15 single-cell RNA-seq data, the relationships between tumor immune dysfunction and exclusion (TIDE) scores and survival prognosis in each patient were calculated and evaluated, and the immune escape mechanism affecting the independent prognosis of LUAD patients was identified. Functional enrichment analysis explored the antitumour immune response and biological behavior of tumor cells among different LUAD groups. Single-cell annotation and pseudotemporal analysis were used to explore the target molecules and immune escape mechanisms of LUAD.

RESULTS

Myeloid-derived suppressor cells (MDSCs) and IRF8 were identified as risk and protective factors for the independent prognosis of LUAD patients, respectively. In the tumor microenvironment of patients with high infiltration of MDSCs, the antitumor immune response is significantly suppressed, while tumor cell division, proliferation, and distant metastasis are significantly enhanced. Single-cell RNA-seq analysis revealed that IRF8 is an important regulator of MDSC differentiation in LUAD myeloid cells. In addition, IRF8 may regulate the differentiation of MDSCs through the IL6-JAK-STAT3 signalling pathway.

CONCLUSIONS

IRF8 deficiency impairs the normal development of LUAD myeloid cells and induces their differentiation into MDSCs, thereby accelerating the immune escape of LUAD cells. IRF8-targeted activation to inhibit the formation of MDSCs may be a new target for immunotherapy in LUAD.

Exploring the prognostic implications of cuproptosis-associated alterations in clear cell renal cell carcinoma via in vitro experiments

This study investigated the impact of novel copper ionophores on the prognosis of clear cell renal cell carcinoma (ccRCC) and the tumor microenvironment (TME). The differential expression of 10 cuproptosis and 40 TME-pathway-related genes were measured in 531 tumor samples and 71 adjacent kidney samples in The Cancer Genome Atlas database. A risk score model was constructed with LASSO cox to predict the prognosis of ccRCC patients. Forest plot and function enrichment were used to study the biological function of the key genes in depth. The study found that the risk score model accurately predicted the prognosis of ccRCC patients. Patients with high scores had higher immune responses with a higher proportion of anti-tumor lymphocytes and a lower proportion of immunosuppressive M2-like macrophages. However, the high-score group also exhibited a higher proportion of T follicular helper cells and regulatory T cells. These results suggest that cuproptosis-based therapy may be worth further investigation for the treatment of ccRCC and TME. Subsequently, by using RNAi, we established the stable depletion models of FDX1 and PDHB in ccRCC cell lines 786-O and ACHN. Through CCK8, colony formation, and Transwell assays, we observed that the knockdown of FDX1 and PDHB could significantly reduce the capabilities of proliferation and migration in ccRCC cells. In conclusion, this study illuminates the potential effectiveness of copper ionophores in the treatment of ccRCC, with higher risk scores correlating with better TME immune responses. It sets the stage for future cuproptosis-based therapy research in ccRCC and other cancers, focusing on copper's role in TME.

CGPA: multi-context insights from the cancer gene prognosis atlas

Cancer transcriptomic data are used extensively to interrogate the prognostic value of targeted genes, yet basic scientists and clinicians have predominantly relied on univariable survival analysis for this purpose. This method often fails to capture the full prognostic potential and contextual relevance of the genes under study, inadvertently omitting a group of genes we term univariable missed-opportunity prognostic (UMOP) genes. Recognizing the complexity of revealing multifaceted prognostic implications, especially when extending the analysis to include various covariates and thresholds, we present the Cancer Gene Prognosis Atlas (CGPA). This platform greatly enhances gene-centric biomarker research across cancer types by offering an interactive and user-friendly interface for highly customized, in-depth prognostic analysis. CGPA notably supports data-driven exploration of gene pairs and gene-hallmark relationships, elucidating key composite biological mechanisms like synthetic lethality and immunosuppression. It further expands its capabilities to assess multi-gene panels using both public and user-provided data, facilitating a seamless mechanism-to-machine analysis. Additionally, CGPA features a designated portal for discovering prognostic gene modules using curated cancer immunotherapy data. Ultimately, CGPA's comprehensive, accessible tools allow cancer researchers, including those without statistical expertise, to precisely investigate the prognostic landscape of genes, customizing the model to fit specific research hypotheses and enhancing biomarker discovery and validation through a synergy of mechanistic and data-driven strategies.

Efficacy comparison of immune combination therapies in subgroups for advanced hepatocellular carcinoma patients: Systematic review and network meta-analysis

BACKGROUND

There is a lack of precision in the immunotherapy strategy tailored for patients exhibiting diverse clinical characteristics. This study aims to employ a rigorous network meta-analysis (NMA) approach to systematically evaluate the effectiveness of immune-combination therapies among patients with advanced hepatocellular carcinoma, taking into account their varying clinico-characteristics.

METHODS

Studies were retrieved from PubMed, Embase, Cochrane Library, and Web of Science databases. The included first-line phase III studies were categorized into three types: immunotherapy combined with anti-angiogenetic agents, immunotherapy combined with tyrosine kinase inhibitors, and dual immunotherapy, with sorafenib serving as the control group. The primary endpoint used to assess efficacy was overall survival (OS), facilitating a comparative analysis among the three treatment modalities. Furthermore, subgroup analyses were conducted to evaluate the varying effectiveness for patients with diverse clinico-characteristics. Secondary outcome measures included progression-free survival, objective response rate, and toxicity assessment.

RESULTS

A total of 6 studies were included in the NMA, encompassing a cohort of 3840 patients. The results revealed that immunotherapy combined with anti-angiogenetic agents exhibited a significantly enhanced therapeutic effect in terms of improving OS compared to sorafenib (HR = 0.61, 95% CrI, 0.42-0.90). Furthermore, based on various clinicopathological features, this combination therapy demonstrated superior OS responses in specific patient subgroups: BCLC C (HR = 0.63, 95% CrI, 0.42-0.93), ECOG 1 (HR = 0.57, 95% CrI, 0.36-0.91), with extrahepatic spread (EHS) (HR = 0.59, 95% CrI, 0.37-0.92), alpha fetoprotein (AFP)<400ng/ml (HR = 0.56, 95% CrI, 0.33-0.94) and viral hepatitis positivity (HR = 0.56, 95% CrI, 0.39-0.77) (especially HBV (HR = 0.58, 95% CrI, 0.40-0.85)). Importantly, the advantage of this combination therapy was even more pronounced in patients with viral hepatitis positivity. Also, the adverse events associated with immunotherapy combined with antiangiogenic drugs were moderate.

CONCLUSIONS

Immunotherapy combined with anti-angiogenetic agents could represent the most effective first-line intervention for achieving improved OS, particularly in patients with viral hepatitis positivity.

Mapping the genetic landscape establishing a tumor immune microenvironment favorable for anti-PD-1 response in mice and humans

Identifying host genetic factors modulating immune checkpoint inhibitor (ICI) efficacy has been experimentally challenging because of variations in both host and tumor genomes, differences in the microbiome, and patient life exposures. Utilizing the Collaborative Cross (CC) multi-parent mouse genetic resource population, we developed an approach that fixes the tumor genomic configuration while varying host genetics. With this approach, we discovered that response to anti-PD-1 (aPD1) immunotherapy was significantly heritable in four distinct murine tumor models (H2 between 0.18-0.40). For the MC38 colorectal carcinoma system (H2 = 0.40), we mapped four significant ICI response quantitative trait loci (QTL) localized to mouse chromosomes (mChr) 5, 9, 15 and 17, and identified significant epistatic interactions between specific QTL pairs. Differentially expressed genes within these QTL were highly enriched for immune genes and pathways mediating allograft rejection and graft vs host disease. Using a cross species analytical approach, we found a core network of 48 genes within the four QTLs that showed significant prognostic value for overall survival in aPD1 treated human cohorts that outperformed all other existing validated immunotherapy biomarkers, especially in human tumors of the previously defined immune subtype 4. Functional blockade of two top candidate immune targets within the 48 gene network, GM-CSF and high affinity IL-2/IL-15 signaling, completely abrogated the MC38 tumor transcriptional response to aPD1 therapy in vivo. Thus, we have established a powerful cross species in vivo platform capable of uncovering host genetic factors that establish the tumor immune microenvironment configuration propitious for ICI response.

DNA methylation profiling deciphers three EMT subtypes with distinct prognoses and therapeutic vulnerabilities in breast cancer

Background: Epithelial-mesenchymal transition (EMT), deemed a pivotal hallmark of tumours, is intricately regulated by DNA methylation and encompasses multiple states along tumour progression. The potential mechanisms that drive the intrinsic heterogeneity of breast cancer (BC) via EMT transformation have not been identified, presenting a significant obstacle in clinical diagnosis and treatment. Methods: A total of 7,602 patients have been included in this study. We leveraged integrated multiomics data (epigenomic, genomic, and transcriptomic data) to delineate the comprehensive landscape of EMT in BC. Subsequently, a subtyping classifier was developed through a machine learning framework proposed by us. Results: We classified the BC samples into three methylation-driven EMT subtypes with distinct features, namely, C1 (the mammary duct development subtype with TP53 activation), C2 (the immune infiltration subtype with high TP53 mutation), and C3 (the ERBB2 amplification subtype with an unfavorable prognosis). Specifically, patients with the C1 subtype might respond to endocrine therapy or the p53-MDM2 antagonist nutlin-3. Patients with the C2 subtype might benefit from combined therapeutic regimens involving radiotherapy, PARP inhibitors, and immune checkpoint blockade therapy. Patients with the C3 subtype might benefit from anti-HER2 agents such as lapatinib. Notably, to increase the clinical applicability of the EMT subtypes, we devised a 96-gene panel-based classifier via a machine learning framework. Conclusions: Our study identified three methylation-driven EMT subtypes with distinct prognoses and biological traits to capture heterogeneity in BC and provided a rationale for the use of this classification as a powerful tool for developing new strategies for clinical trials.

RNA vaccines for cancer: Principles to practice

Vaccines are the most impactful medicines to improve health. Though potent against pathogens, vaccines for cancer remain an unfulfilled promise. However, recent advances in RNA technology coupled with scientific and clinical breakthroughs have spurred rapid discovery and potent delivery of tumor antigens at speed and scale, transforming cancer vaccines into a tantalizing prospect. Yet, despite being at a pivotal juncture, with several randomized clinical trials maturing in upcoming years, several critical questions remain: which antigens, tumors, platforms, and hosts can trigger potent immunity with clinical impact? Here, we address these questions with a principled framework of cancer vaccination from antigen detection to delivery. With this framework, we outline features of emergent RNA technology that enable rapid, robust, real-time vaccination with somatic mutation-derived neoantigens-an emerging "ideal" antigen class-and highlight latent features that have sparked the belief that RNA could realize the enduring vision for vaccines against cancer.

Integrative analysis of genomic and epigenomic regulation reveals miRNA mediated tumor heterogeneity and immune evasion in lower grade glioma

The expression dysregulation of microRNAs (miRNA) has been widely reported during cancer development, however, the underling mechanism remains largely unanswered. In the present work, we performed a systematic integrative study for genome-wide DNA methylation, copy number variation and miRNA expression data to identify mechanisms underlying miRNA dysregulation in lower grade glioma. We identify 719 miRNAs whose expression was associated with alterations of copy number variation or promoter methylation. Integrative multi-omics analysis revealed four subtypes with differing prognoses. These glioma subtypes exhibited distinct immune-related characteristics as well as clinical and genetic features. By construction of a miRNA regulatory network, we identified candidate miRNAs associated with immune evasion and response to immunotherapy. Finally, eight prognosis related miRNAs were validated to promote cell migration, invasion and proliferation through in vitro experiments. Our study reveals the crosstalk among DNA methylation, copy number variation and miRNA expression for immune regulation in glioma, and could have important implications for patient stratification and development of biomarkers for immunotherapy approaches.

Immune Phenotype-Genotype Associations in Primary Clear Cell Renal Cell Carcinoma and Matched Metastatic Tissue

Adjuvant immunotherapy has been recently recommended for patients with metastatic clear cell renal cell carcinoma (ccRCC), but there are no tissue biomarkers to predict treatment response in ccRCC. Potential predictive biomarkers are mainly assessed in primary tumor tissue, whereas metastases (METs) remain understudied. To explore potential differences between genomic alterations and immune phenotypes in primary tumors and their matched METs, we analyzed primary tumors (PTs) of 47 ccRCC patients and their matched distant METs by comprehensive targeted parallel sequencing, whole-genome copy number variation analysis, determination of microsatellite instability, and tumor mutational burden. We quantified the spatial distribution of tumor-infiltrating CD8+ T cells and coexpression of the T-cell-exhaustion marker thymocyte selection-associated high mobility group box (TOX) by digital immunoprofiling and quantified tertiary lymphoid structures. Most METs were pathologically "cold." Inflamed, pathologically "hot" PTs were associated with decreased disease-free survival, worst for patients with high levels of CD8+TOX+ T cells. Interestingly, inflamed METs showed a relative increase in exhausted CD8+TOX+ T cells and increased accumulative size of tertiary lymphoid structures compared with PTs. Integrative analysis of molecular and immune phenotypes revealed BAP1 and CDKN2A/B deficiency to be associated with an inflamed immune phenotype. Our results highlight the distinct spatial distribution and differentiation of CD8+ T cells at metastatic sites, and the association of an inflamed microenvironment with specific genomic alterations.

RNA modification gene WDR4 facilitates tumor progression and immunotherapy resistance in breast cancer

INTRODUCTION

Growing interest toward RNA modification in cancer has inspired the exploration of gene sets related to multiple RNA modifications. However, a comprehensive elucidation of the clinical value of various RNA modifications in breast cancer is still lacking.

OBJECTIVES

This study aimed to provide a strategy based on RNA modification-related genes for predicting therapy response and survival outcomes in breast cancer patients.

METHODS

Genes related to thirteen RNA modification patterns were integrated for establishing a nine-gene-containing signature-RMscore. Alterations of tumor immune microenvironment and therapy response featured by different RMscore levels were assessed by bulk transcriptome, single-cell transcriptome and genomics analyses. The biological function of key RMscore-related molecules was investigated by cellular experiments in vitro and in vivo, using flow cytometry, immunohistochemistry and immunofluorescence staining.

RESULTS

This study has raised an effective therapy strategy for breast cancer patients after a well-rounded investigation of RNA modification-related genes. With a great performance of predicting patient prognosis, high levels of the RMscore proposed in this study represented suppressive immune microenvironment and therapy resistance, including adjuvant chemotherapy and PD-L1 blockade treatment. As the key contributor of the RMscore, inhibition of WDR4 impaired breast cancer progression significantly in vitro and in vivo, as well as participated in regulating cell cycle and mTORC1 signaling pathway via m7G modification.

CONCLUSION

Briefly, this study has developed promising and effective tactics to achieve the prediction of survival probabilities and treatment response in breast cancer patients.

Weighted centroid trees: a general approach to summarize phylogenies in single-labeled tumor mutation tree inference

MOTIVATION

Tumor trees, which depict the evolutionary process of cancer, provide a backbone for discovering recurring evolutionary processes in cancer. While they are not the primary information extracted from genomic data, they are valuable for this purpose. One such extraction method involves summarizing multiple trees into a single representative tree, such as consensus trees or supertrees.

RESULTS

We define the "weighted centroid tree problem" to find the centroid tree of a set of single-labeled rooted trees through the following steps: (i) mapping the given trees into the Euclidean space, (ii) computing the weighted centroid matrix of the mapped trees, and (iii) finding the nearest mapped tree (NMTP) to the centroid matrix. We show that this setup encompasses previously studied parent-child and ancestor-descendent metrics as well as the GraPhyC and TuELiP consensus tree algorithms. Moreover, we show that, while the NMTP problem is polynomial-time solvable for the adjacency embedding, it is NP-hard for ancestry and distance mappings. We introduce integer linear programs for NMTP in different setups where we also provide a new algorithm for the case of ancestry embedding called 2-AncL2, that uses a novel weighting scheme for ancestry signals. Our experimental results show that 2-AncL2 has a superior performance compared to available consensus tree algorithms. We also illustrate our setup's application on providing representative trees for a large real breast cancer dataset, deducing that the cluster centroid trees summarize reliable evolutionary information about the original dataset.

AVAILABILITY AND IMPLEMENTATION

https://github.com/vasei/WAncILP.

Characteristics of the immune environment in prostate cancer as an adjunct to immunotherapy

Background and Aims

The tumor microenvironment (TME) exerts an important role in carcinogenesis and progression. Several investigations have suggested that immune cell infiltration (ICI) is of high prognostic importance for tumor progression and patient survival in many tumors, particularly prostate cancer. The pattern of immune infiltration of PCa, on the other hand, has not been thoroughly understood.

Methods

The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets on PCa were obtained, and several datasets were merged into one data set using the "ComBat" algorithm. The ICI profiles of PCa patients were then to be uncovered by two computer techniques. The unsupervised clustering method was utilized to identify three ICI patterns in tumor samples, and Principal Component Analysis (PCA) was conducted to estimate the ICI score.

Results

Three different clusters of three ICIs were identified in 1341 PCa samples, which also correlated with different clinical features/characteristics and biological pathways. Patients with PCa are classified into high and low subtypes based on the ICI scores extracted from immune-associated signature genes. High ICI score subtypes are associated with a worse prognosis, which may intrigue the activation of cancer-related and immune-related pathways such as pathways involving Toll-like receptors, T-cell receptors, JAK-STAT, and natural killer cells. The ICI score was linked to tumor mutation load and immune/cancer-relevant signaling pathways, which explain prostate cancer's poor prognosis.

Conclusion

The findings of this study not only advanced our knowledge of the mechanism of immune response in the prostate tumor microenvironment but also provided a novel biomarker, that is, the ICI score, for disease prognosis and guiding precision immunotherapy.

The tumor microenvironment of benign and malignant salivary gland tumors

BACKGROUND

Treatment of salivary gland tumors (SGTs) remains challenging. Little is known about the immune landscape of SGTs. We aimed to characterize the tumor microenvironment in benign and malignant SGTs.

METHODS

Eleven benign and nine malignant tumors were collected from patients undergoing curative intent surgery. Specimens were analyzed using mass cytometry by time-of-flight. Immune cell populations were manually gated, and T cells were clustered using the FlowSOM algorithm. Population frequencies were compared between high-grade and low-grade malignancies, corrected for multiple hypothesis testing.

RESULTS

There were trends towards increased CD4+ and CD8+ T cells among malignant tumors. High-grade malignancies exhibited trends towards higher frequencies of CD8+ PD-1+ CD39+ CD103+ exhausted T cells, CD4+ FoxP3+ TCF-1+ CD127- Tregs, and CD69+ CD25- CD4+ T cells compared to low-grade malignancies.

CONCLUSION

SGTs exhibit significant immunologic diversity. High-grade malignancies tended to have greater infiltration of exhausted CD8+ T cells and Tregs, which may guide future studies for immunotherapy strategies.

A Deep Learning-Based Assessment Pipeline for Intraepithelial and Stromal Tumor-Infiltrating Lymphocytes in High-Grade Serous Ovarian Carcinoma

Tumor-infiltrating lymphocytes (TILs) are associated with improved survival in patients with epithelial ovarian cancer. However, TIL evaluation has not been used in routine clinical practice because of reproducibility issues. The current study developed two convolutional neural network models to detect TILs and to determine their spatial location in whole slide images, and established a spatial assessment pipeline to objectively quantify intraepithelial and stromal TILs in patients with high-grade serous ovarian carcinoma. The predictions of the established models showed a significant positive correlation with the number of CD8+ T cells and immune gene expressions. Patients with a higher density of intraepithelial TILs had a significantly prolonged overall survival and progression-free survival in multiple cohorts. On the basis of the density of intraepithelial and stromal TILs, patients were classified into three immunophenotypes: immune inflamed, excluded, and desert. The immune-desert subgroup showed the worst prognosis. Gene expression analysis showed that the immune-desert subgroup had lower immune cytolytic activity and T-cell-inflamed gene-expression profile scores, whereas the immune-excluded subgroup had higher expression of interferon-γ and programmed death 1 receptor signaling pathway. The established evaluation method provided detailed and comprehensive quantification of intraepithelial and stromal TILs throughout hematoxylin and eosin-stained slides. It has potential for clinical application for personalized treatment of patients with ovarian cancer.

Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours

Although more than a decade has passed since the approval of immune checkpoint inhibitors (ICIs) for the treatment of melanoma and non-small-cell lung, breast and gastrointestinal cancers, many patients still show limited response. US Food and Drug Administration (FDA)-approved biomarkers include programmed cell death 1 ligand 1 (PDL1) expression, microsatellite status (that is, microsatellite instability-high (MSI-H)) and tumour mutational burden (TMB), but these have limited utility and/or lack standardized testing approaches for pan-cancer applications. Tissue-based analytes (such as tumour gene signatures, tumour antigen presentation or tumour microenvironment profiles) show a correlation with immune response, but equally, these demonstrate limited efficacy, as they represent a single time point and a single spatial assessment. Patient heterogeneity as well as inter- and intra-tumoural differences across different tissue sites and time points represent substantial challenges for static biomarkers. However, dynamic biomarkers such as longitudinal biopsies or novel, less-invasive markers such as blood-based biomarkers, radiomics and the gut microbiome show increasing potential for the dynamic identification of ICI response, and patient-tailored predictors identified through neoadjuvant trials or novel ex vivo tumour models can help to personalize treatment. In this Perspective, we critically assess the multiple new static, dynamic and patient-specific biomarkers, highlight the newest consortia and trial efforts, and provide recommendations for future clinical trials to make meaningful steps forwards in the field.

Deciphering lung adenocarcinoma prognosis and immunotherapy response through an AI-driven stemness-related gene signature

Lung adenocarcinoma (LUAD) is a leading cause of cancer-related deaths, and improving prognostic accuracy is vital for personalised treatment approaches, especially in the context of immunotherapy. In this study, we constructed an artificial intelligence (AI)-driven stemness-related gene signature (SRS) that deciphered LUAD prognosis and immunotherapy response. CytoTRACE analysis of single-cell RNA sequencing data identified genes associated with stemness in LUAD epithelial cells. An AI network integrating traditional regression, machine learning, and deep learning algorithms constructed the SRS based on genes associated with stemness. Subsequently, we conducted a comprehensive exploration of the connection between SRS and both intrinsic and extrinsic immune environments using multi-omics data. Experimental validation through siRNA knockdown in LUAD cell lines, followed by assessments of proliferation, migration, and invasion, confirmed the functional role of CKS1B, a top SRS gene. The SRS demonstrated high precision in predicting LUAD prognosis and likelihood of benefiting from immunotherapy. High-risk groups classified by the SRS exhibited decreased immunogenicity and reduced immune cell infiltration, indicating challenges for immunotherapy. Conversely, in vitro experiments revealed CKS1B knockdown significantly impaired aggressive cancer phenotypes like proliferation, migration, and invasion of LUAD cells, highlighting its pivotal role. These results underscore a close association between stemness and tumour immunity, offering predictive insights into the immune landscape and immunotherapy responses in LUAD. The newly established SRS holds promise as a valuable tool for selecting LUAD populations likely to benefit from future clinical stratification efforts.