Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer

The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden

Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a significant threat to human health. Recently proposed immunotherapy checkpoint blockade treatments have proven effective for CRC, but their use depends on measuring specific biomarkers in patients. Among these biomarkers, tumor mutational burden (TMB) has emerged as a novel indicator, traditionally requiring next-generation sequencing for measurement, which is time-consuming, labor intensive, and costly. To provide an economical and rapid way to predict patients' TMB, the KMeansGraphMIL model was proposed based on weakly supervised multiple-instance learning. Compared with previous weakly supervised multiple-instance learning models, KMeansGraphMIL leveraged both the similarity of image patch feature vectors and the spatial relationships between patches. This approach improved the model's area under the receiver operating characteristic curve to 0.8334 and significantly increased the recall to 0.7556. Thus, this study presents an economical and rapid framework for predicting CRC TMB, offering the potential for physicians to quickly develop treatment plans and saving patients substantial time and money.

High tumor mutation burden mitigates the negative impact of chemotherapy history on immune checkpoint blockade therapy

Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small-cell lung cancer (NSCLC) accounting for the majority of cases. Immune checkpoint inhibitor (ICI) therapy, particularly with PD-1 inhibitors like nivolumab, has become a critical treatment option for advanced NSCLC. ICI therapy has revolutionized treatment, but prior chemotherapy may diminish ICI treatment efficacy. Tumor mutation burden (TMB) has emerged as a crucial predictor of ICI response, yet its interaction with chemotherapy history in ICI therapy is not fully understood. In this study, I investigate the impact of chemotherapy history on ICI treatment outcomes, focusing on TMB as a potential mitigating factor. Analyzing data from 512 patients with advanced NSCLC treated with PD-1/PD-L1 or CTLA-4 inhibitors, this sudy found that prior chemotherapy significantly reduced objective response rates (ORR) to ICI therapy, particularly in patients with low TMB (<15 mut/Mb). However, in patients with high TMB (≥15 mut/Mb), the negative impact of chemotherapy history on ICI treatment efficacy is minimal, suggesting that high TMB mitigates chemotherapy-induced resistance to ICI therapy. Furthermore, while chemotherapy history is associated with worse overall survival (OS) and progression-free survival (PFS) following ICI therapy in low-TMB patients, no such association is observed in high-TMB patients. These findings highlight the importance of TMB as a predictive biomarker, emphasizing the need for optimal treatment sequencing and personalized therapeutic strategies to overcome chemotherapy-induced immune resistance and maximize ICI treatment efficacy. These results suggest that ICI therapy may be more beneficial as a first-line treatment, particularly for patients with low TMB.

Identification of a long non-coding RNA signature associated with cuproptosis for prognosis and immunotherapy response prediction in patients with lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD), the most common histotype of lung cancer, exhibits high heterogeneity due to molecular variations. Cuproptosis is a newly discovered type of cell death that is linked to copper metabolism and long non-coding RNAs (lncRNAs) may play a significant role in this process. We conducted a comprehensive analysis of lncRNA related to cuproptosis and identified a CRLscore to predict the prognosis and immune landscape for LUAD patients.

METHODS

The LUAD patient cohort obtained from TCGA database was divided into training and validation sets. A range of statistical methods were employed to identify lncRNAs associated with cuproptosis. Multivariate Cox regression was then utilized to develop the CRLscore, which was further used to construct and evaluate a nomogram. Additionally, we investigated the biological functions, gene mutations, and immune landscape.

RESULTS

A CRLscore, comprising six cuproptosis-related lncRNAs, was developed to stratify patients into high- and low-risk groups. The CRLscore demonstrated its ability to independently predict prognosis in both the training set and the validation set. Utilizing the CRLscore, we constructed a nomogram that exhibited favorable predictive efficiency. Furthermore, the cuproptosis-related lncRNAs exhibited associations with important signaling pathways such as p53 signaling, MYC Targets V1, and G2M Checkpoint. Notably, the CRLscore displayed substantial differences in somatic mutations and immune landscape. Finally, qRT-PCR results showed the significant differential expression of five cuproptosis-related lncRNAs between LUAD and normal cells.

CONCLUSION

The CRLscore could serve as a potential prognostic indicator and may predict the response to immunotherapy in LUAD patients.

Gamma delta T cells and their immunotherapeutic potential in cancer

Gamma-delta (γδ) T cells are a unique subset of T lymphocytes that play diverse roles in immune responses, bridging innate and adaptive immunity. With growing interest in their potential for cancer immunotherapy, a comprehensive and inclusive exploration of γδ T cell families, their development, activation mechanisms, functions, therapeutic implications, and current treatments is essential. This review aims to provide an inclusive and thorough discussion of these topics. Through our discussion, we seek to uncover insights that may harbinger innovative immunotherapeutic strategies. Beginning with an overview of γδ T cell families including Vδ1, Vδ2, and Vδ3, this review highlights their distinct functional properties and contributions to anti-tumor immunity. Despite γδ T cells exhibiting both anti-tumor and pro-tumor activities, our review elucidates strategies to harness the anti-tumor potential of γδ T cells for therapeutic benefit. Moreover, our paper discusses the structural intricacies of the γδ T cell receptor and its significance in tumor recognition. Additionally, this review examines conventional and emerging γδ T cell therapies, encompassing both non-engineered and engineered approaches, with a focus on their efficacy and safety profiles in clinical trials. From multifunctional capabilities to diverse tissue distribution, γδ T cells play a pivotal role in immune regulation and surveillance. By analyzing current research findings, this paper offers insights into the dynamic landscape of γδ T cell-based immunotherapies, underscoring their promise as a potent armamentarium against cancer. Furthermore, by dissecting the complex biology of γδ T cells, we learn valuable information about the anti-cancer contributions of γδ T cells, as well as potential targets for immunotherapeutic interventions.

Pan-cancer analysis of co-inhibitory molecules revealing their potential prognostic and clinical values in immunotherapy

Background

The widespread use of immune checkpoint inhibitors (anti-CTLA4 or PD-1) has opened a new chapter in tumor immunotherapy by providing long-term remission for patients. Unfortunately, however, these agents are not universally available and only a minority of patients respond to them. Therefore, there is an urgent need to develop novel therapeutic strategies targeting other co-inhibitory molecules. However, comprehensive information on the expression and prognostic value of co-inhibitory molecules, including co-inhibitory receptors and their ligands, in different cancers is not yet available.

Methods

We investigated the expression, correlation, and prognostic value of co-inhibitory molecules in different cancer types based on TCGA, UCSC Xena, TIMER, CellMiner datasets. We also examined the associations between the expression of these molecules and the extent of immune cell infiltration. Besides, we conducted a more in-depth study of VISTA.

Result

The results of differential expression analysis, correlation analysis, and drug sensitivity analysis suggest that CTLA4, PD-1, TIGIT, LAG3, TIM3, NRP1, VISTA, CD80, CD86, PD-L1, PD-L2, PVR, PVRL2, FGL1, LGALS9, HMGB1, SEMA4A, and VEGFA are associated with tumor prognosis and immune cell infiltration. Therefore, we believe that they are hopefully to serve as prognostic biomarkers for certain cancers. In addition, our analysis indicates that VISTA plays a complex role and its expression is related to TMB, MSI, cancer cell stemness, DNA/RNA methylation, and drug sensitivity.

Conclusions

These co-inhibitory molecules have the potential to serve as prognostic biomarkers and therapeutic targets for a broad spectrum of cancers, given their strong associations with key clinical metrics. Furthermore, the analysis results indicate that VISTA may represent a promising target for cancer therapy.

Global research trends of tumor microenvironment in non-small cell lung cancer with epidermal growth factor receptor mutation: a bibliometric analysis from 2014 to 2023

Purpose

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, and about half of the patients had mutations in the epidermal growth factor receptor (EGFR) gene. Changes in the tumor microenvironment after EGFR mutation are closely related to tumor progression and treatment efficacy.

Materials and methods

We searched the Web of Science Core Collection database to select the articles related to tumor microenvironment in non-small cell lung cancer with epidermal growth factor receptor mutation. The countries/regions, institutes, authors, journals, references, and keywords were visualized and analyzed.

Results

227 relevant studies were obtained from WoSCC. These articles came from 102 countries and 1179 institutions. After network analysis, it was found that the intensity of USA cooperation with China was the greatest (LS=13), followed by cooperation with South Korea (LS=3) and with Japan (LS=3). A total of 2267 authors participated the all 227 articles. 112 journals were covered, and Frontiers in Oncology published most papers (n=16, 14.3%). A total of 7964 co-cited references are related to TME in NSCLC with EGFR mutation. "EGFR" is the keyword with the highest centrality (C=0.31) and first appeared. The keywords that burst in the last 1 year (2022-2023) are "immunotherapy", "mechanism", "lung neoplasms", "T cells", and "multicenter".

Conclusion

Effective drug treatment of advanced NSCLC with EGFR mutations after failure of first-line chemotherapy is one of the hotspots, in which the efficacy of immune checkpoint inhibitors may be the direction of the current and future studies that need to find a breakthrough.

Whole genome sequencing of 378 prostate cancer metastases reveals tissue selectivity for mismatch deficiency with potential therapeutic implications

BACKGROUND

Survival of patients with metastatic castration-resistant prostate cancer (mCRPC) depends on the site of metastatic dissemination.

METHODS

Patients with mCRPC were prospectively included in the CPCT-02 metastatic site biopsy study. We evaluated whole genome sequencing (WGS) of 378 mCRPC metastases to understand the genetic traits that affect metastatic site distribution.

RESULTS

Our findings revealed that RB1, PIK3CA, JAK1, RNF43, and TP53 mutations are the most frequent genetic determinants associated with site selectivity for metastatic outgrowth. Furthermore, we explored mutations in the non-coding genome and found that androgen receptor (AR) chromatin binding sites implicated in metastatic prostate cancer differ in mutation frequencies between metastatic sites, converging on pathways that impact DNA repair. Notably, liver and visceral metastases have a higher tumor mutational load (TML) than bone and lymph node metastases, independent of genetic traits associated with neuroendocrine differentiation. We found that TML is strongly associated with DNA mismatch repair (MMR)-deficiency features in these organs.

CONCLUSIONS

Our results revealed gene mutations that are significantly associated with metastatic site selectivity and that frequencies of non-coding mutations at AR chromatin binding sites differ between metastatic sites. Immunotherapeutics are thus far unsuccessful in unselected mCRPC patients. We found a higher TML in liver and visceral metastases compared to bone and lymph node metastases. As immunotherapeutics response is associated with mutational burden, these findings may assist in selecting mCRPC patients for immunotherapy treatment based on organs affected by metastatic disease.

TRIAL REGISTRATION NUMBER

NCT01855477.

Endogenous viral elements constitute a complementary source of antigens for personalized cancer vaccines

Personalized cancer vaccines (PCVs) largely leverage neoantigens arising from somatic mutations, limiting their application to patients with relatively high tumor mutational burden (TMB). This underscores the need for alternative antigens to design PCVs for low TMB cancers. To this end, we substantiate endogenous retroviral elements (EVEs) as tumor antigens through large-scale genomic analyses of healthy tissues and solid cancers. These analyses revealed that the breadth of EVE expression in tumors stratify checkpoint inhibitor-treated melanoma patients into groups with differential overall and progression-free survival. To enable the design of PCVs containing EVE-derived epitopes with therapeutic potential, we developed a computational pipeline, ObsERV. We show that EVE-derived peptides are presented as epitopes on tumors and can be predicted by ObsERV. Preclinical testing of ObsERV demonstrates induction of sustained poly-functional CD4+ and CD8+ T-cell responses as well as long-term tumor protection. As such, EVEs may facilitate and improve PCVs, especially for low-TMB patients.

Overview on biomarkers for immune oncology drugs

Although immune checkpoint inhibitors (ICIs) are widely used in clinical oncology, less than half of treated cancer patients derive benefit from this therapy. Both tumor- and host-related variables are implicated in response to ICIs. The predictive value of PD-L1 expression is confined only to several cancer types, so this molecule is not an agnostic biomarker. Highly elevated tumor mutation burden (TMB) caused either by excessive carcinogenic exposure or by a deficiency in DNA repair is a reliable indicator for ICI efficacy, as exemplified by tumors with high-level microsatellite instability (MSI-H). Other potentially relevant tumor-related characteristics include gene expression signatures, pattern of tumor infiltration by immune cells, and, perhaps, some immune-response modifying somatic mutations. Host-related factors have not yet been comprehensively considered in relevant clinical trials. Microbiome composition, markers of systemic inflammation [e.g., neutrophil-to-lymphocyte ratio (NLR)], and human leucocyte antigen (HLA) diversity may influence the efficacy of ICIs. Studies on ICI biomarkers are likely to reveal modifiable tumor or host characteristics, which can be utilized to direct the antitumor immune defense. Examples of the latter approach include tumor priming to immune therapy by cytotoxic drugs and elevation of ICI efficacy by microbiome modification.

Multi-cohort validation based on a novel prognostic signature of anoikis for predicting prognosis and immunotherapy response of esophageal squamous cell carcinoma

Immunotherapy is recognized as an effective and promising treatment modality that offers a new approach to cancer treatment. However, identifying responsive patients remains challenging. Anoikis, a distinct form of programmed cell death, plays a crucial role in cancer progression and metastasis. Thus, we aimed to investigate prognostic biomarkers based on anoikis and their role in guiding immunotherapy decisions for esophageal squamous cell carcinoma (ESCC). By consensus clustering, the GSE53624 cohort of ESCC patients was divided into two subgroups based on prognostic anoikis-related genes (ARGs), with significant differences in survival outcomes between the two subgroups. Subsequently, we constructed an ARGs signature with four genes, and its reliability and accuracy were validated both internally and externally. Additional, different risk groups showed notable variances in terms of immunotherapy response, tumor infiltration, functional enrichment, immune function, and tumor mutation burden. Notably, the effectiveness of the signature in predicting immunotherapy response was confirmed across multiple cohorts, including GSE53624, GSE53625, TCGA-ESCC, and IMvigor210, highlighting its potential utility in predicting immunotherapy response. In conclusion, the ARGs signature has the potential to serve as an innovative and dependable prognostic biomarker for ESCC, facilitating personalized treatment strategies in this field, and may represent a valuable new tool for guiding ESCC immunotherapy decision-making.

T-cell receptors identified by a personalized antigen-agnostic screening approach target shared neoantigen KRAS Q61H

Adoptive cell therapy (ACT) with TCR-engineered T-cells represents a promising alternative to TIL- or CAR-T therapies for patients with advanced solid cancers. Currently, selection of therapeutic TCRs critically depends on knowing the target antigens, a condition excluding most patients from treatment. Direct antigen-agnostic identification of tumor-specific T-cell clonotypes and TCR-T manufacturing using their TCRs can advance ACT for patients with aggressive solid cancers. We present a method to identify tumor-specific clonotypes from surgical specimens by comparing TCRβ-chain repertoires of TILs and adjacent tissue-resident lymphocytes. In six out of seven NSCLC-patients analyzed, our selection of tumor-specific clonotypes based on TIL-abundance and high tumor-to-nontumor frequency ratios was confirmed by gene expression signatures determined by scRNA-Seq. In three patients, we demonstrated that predicted tumor-specific clonotypes reacted against autologous tumors. For one of these patients, we engineered TCR-T cells with four candidate tumor-specific TCRs that showed reactivity against the patient's tumor and HLA-matched NSCLC cell lines. The TCR-T cells were then used to screen for candidate neoantigens and aberrantly expressed antigens. Three TCRs recognized recurrent driver-mutation KRAS Q61H-peptide ILDTAGHEEY presented by HLA-A*01:01. The TCRs were also dominant in a tumor relapse, one was found in cell free DNA. The finding of homologous TCRs in independent KRAS Q61H-positive cancers suggests a therapeutic opportunity for HLA-matched patients with KRAS Q61H-expressing tumors.

Immunotherapy in advanced, KRAS G12C-mutant non-small-cell lung cancer: current strategies and future directions

Kirsten rat sarcoma (KRAS) mutations are present in up to 25% of non-small-cell lung cancer (NSCLC). KRAS G12C is the most common type of mutation, representing approximately half of the cases in KRAS-mutant NSCLC. Mutations in KRAS activate the RAF-MEK-ERK pathway, leading to increased cell proliferation and survival. Recent advances in drug development have led to the approval of KRAS G12C inhibitors sotorasib and adagrasib. This review explores the emerging therapeutic strategies in KRAS G12C-mutant NSCLC, including dual checkpoint blockade and combinations with checkpoint inhibitors, with a focus on the setting of advanced disease.

Immune Checkpoint Blockade Delays Cancer Development and Extends Survival in DNA Polymerase Mutator Syndromes

Mutations in the exonuclease domains of the replicative nuclear DNA polymerases POLD1 and POLE are associated with increased cancer incidence, elevated tumor mutation burden (TMB), and enhanced response to immune checkpoint blockade (ICB). Although ICB is approved for treatment of several cancers, not all tumors with elevated TMB respond, highlighting the need for a better understanding of how TMB affects tumor biology and subsequently immunotherapy response. To address this, we generated mice with germline and conditional mutations in the exonuclease domains of Pold1 and Pole. Engineered mice with Pold1 and Pole mutator alleles presented with spontaneous cancers, primarily lymphomas, lung cancer, and intestinal tumors, whereas Pold1 mutant mice also developed tail skin carcinomas. These cancers had highly variable tissue type-dependent increased TMB with mutational signatures associated with POLD1 and POLE mutations found in human cancers. The Pold1 mutant tail tumors displayed increased TMB; however, only a subset of established tumors responded to ICB. Similarly, introducing the mutator alleles into mice with lung cancer driven by mutant Kras and Trp53 deletion did not improve survival, whereas passaging these tumor cells in vitro without immune editing and subsequently implanting them into immunocompetent mice caused tumor rejection in vivo. These results demonstrated the efficiency by which cells with antigenic mutations are eliminated in vivo. Finally, ICB treatment of mutator mice earlier, before observable tumors had developed delayed cancer onset, improved survival and selected for tumors without aneuploidy, suggesting the potential of ICB in high-risk individuals for cancer prevention. Significance: Treating high-mutation burden mice with immunotherapy prior to cancer onset significantly improves survival, raising the possibility of utilizing immune checkpoint blockade for cancer prevention, especially in individuals with increased risk.

Exome sequencing shows same pattern of clonal tumor mutational burden, intratumor heterogenicity and clonal neoantigen between autologous tumor and Vigil product

Retrospective data support overall survival (OS) advantage to high clonal tumor mutation burden (cTMB), high clonal neoantigen load (cNEO) and low intratumor heterogeneity (ITH) in cancer patients who receive immunotherapy. In order to explore this relationship prospectively with Vigil, a triple function targeted immunotherapy involving ovarian cancer patients in long term follow up of the Phase 2b VITAL trial, we developed an exome sequencing procedure and associated bioinformatics pipeline to determine clonal signal patterns. DNA libraries containing exome sequences tagged with unique molecular identifiers (UMI) were prepared from paired samples and sequenced on Illumina sequencers to high coverage depths of ~ 930X (tumor) and ~ 130X (normal). Raw sequence reads were processed into optimized binary alignment map (BAM) files, using the UMI information. The BAM files were inputted into modules for calling MHC-I alleles, annotating single nucleotide variants (SNVs) and small insertions/deletions (InDels), and for determination of allelic copy number. The outputs were used to predict the sequence of peptide neoantigens and to perform clonality analysis in order to assign each SNV and InDel in a patient tumor sample to a primary clone or subclone. The Clonal Neoantigen pipeline was further assessed using whole exome Illumina sequencing data from three previously published studies. Evaluation of the pipeline using synthetic sequencing data from a sub-clonal deconvolution tool benchmarking study, showed positive predictive value (PPV) and positive percent agreement (PPA) of > 97.5% and > 96.5%, respectively, for SNV and InDel detection with minimum requirements for variant density and allele fraction. Haplotype calls from the Clonal Neoantigen pipeline MHC-I/ MHC-II typing module matched a published benchmark for 91.5% of the calls in a sample of 99 patients. Analysis of exome sequencing data from 14 patients with advanced melanoma revealed a strong correlation between cTMB values determined by the Clonal Neoantigen pipeline as compared to those calculated from the published data (R2 = 0.99). Following validation, the wet lab process and Clonal Neoantigen pipeline was applied to a set of matched normal, tumor, and Vigil product samples from 9 (n = 27 samples) ovarian cancer subjects entered into the VITAL (CL-PTL-119) trial. Results demonstrated marked correlation (R2 = 0.98) of cTMB between tumor used to construct Vigil and Vigil product. Correlation between tumor and Vigil for the cNEO and ITH metrics, showed R2 values of 0.95 and 0.87, respectively. The consistency of the Clonal Neoantigen pipeline results with previously published data as well as the agreement between results for tumor and Vigil for the entire system provide a strong basis of support for utilization of this pipeline for prospective determination of cTMB, cNEO, and ITH values in clinical tumor tissue in order to explore possible correlative relationships with clinical response parameters.

Low-coverage whole genome sequencing of cell-free DNA to predict and track immunotherapy response in advanced non-small cell lung cancer

BACKGROUND

Outcomes under anti-PD-(L)1 therapy have been variable in advanced non-small cell lung cancer (NSCLC) without reliable predictive biomarkers so far. Targeted next-generation sequencing (NGS) of circulating tumor DNA (ctDNA) has demonstrated potential clinical utility to support clinical decisions, but requires prior tumor genetic profiling for proper interpretation, and wide adoption remains limited due to high costs.

METHODS

Tumor-agnostic low-coverage ctDNA whole genome sequencing (lcWGS) was used to longitudinally track genome-wide copy number variations (CNVs) and fragmentation features in advanced NSCLC patients (n = 118 samples from 49 patients) and healthy controls (n = 57). Tumor PD-L1 expression was available for comparison.

FINDINGS

Fragmentation features and CNVs were complementary indicators, whose combination significantly increased ctDNA detection compared to single-marker assessments (+ 20.3% compared to CNV analysis alone). Baseline fragment length alterations, but not CNVs, were significantly associated with subsequent progression-free survival (PFS; hazard ratio [HR] = 4.10, p = 6.58e-05) and could improve PFS predictions based on tumor PD-L1 expression alone (HR = 2.70, p = 0.019). Residual CNVs or aberrant fragmentation of ctDNA under ongoing therapy could stratify patients according to the subsequent response duration (median 5.8 vs. 47.0 months, p = 1.13e-06). The integrative analysis of ctDNA fragment characteristics at baseline, tumor PD-L1 expression, and residual ctDNA under ongoing treatment constituted the strongest independent predictor of PFS (p = 6.25e-05) and overall survival (p = 1.3e-03) in multivariable analyses along with other clinicopathologic variables.

INTERPRETATION

This study demonstrates the feasibility and potential clinical utility of lcWGS for the tumor-agnostic stratification and monitoring of advanced NSCLC under PD-(L)1 blockade based on CNV and fragmentomic profiling.

Pan-Cancer Molecular Biomarkers: Practical Considerations for the Surgical Pathologist

Traditional anatomic pathologic classification of cancer is based on tissue of origin and morphologic and immunohistochemical characterization of the malignant cells. With the technological improvements of massively parallel or next-generation sequencing, oncogenic drivers that are shared across different tumor types are increasingly being identified and used as pan-cancer biomarkers. This approach is reflected in the growing list of Food and Drug Administration-approved tumor-agnostic therapies, including pembrolizumab in the setting of microsatellite instability and high tumor mutational burden, larotrectinib and entrectinib for solid tumors with NTRK fusions, and combined dabrafenib-trametinib for BRAF V600E-mutated neoplasms. Several other biomarkers are currently under investigation, including fibroblast growth factor receptor (FGFR), RET, and ROS1 fusions; ERBB2 amplification; and mutations in the AKT1/2/3, NF1, RAS pathway and (mitogen-activated protein kinase (MAPK) pathway. As molecular assays are increasingly incorporated into routine tumor workup, the emergence of additional pan-cancer biomarkers is likely to be a matter more of "when" than "if." In this review, we first explore some of the conceptual and technical considerations at the intersection of surgical and molecular pathology, followed by a brief overview of both established and emerging molecular pan-cancer biomarkers and their diagnostic and clinical applications.

Unveiling ac4C modification pattern: a prospective target for improving the response to immunotherapeutic strategies in melanoma

Emerging evidence has confirmed the inextricable connection between N4-acetylcytidine (ac4C) mRNA modification and the clinical characteristics of malignancies. Nonetheless, it is uncertain whether and how ac4C mRNA modification patterns affect clinical outcomes in melanoma patients. This research integrated single-cell sequencing data and transcriptomics to pinpoint ac4C-related genes (acRG) linked to melanoma progression and evaluate their clinical implications. Cells with elevated acRG score were predominantly located within the melanocytes cluster. Intercellular communications between melanocytes and other cell subtypes were markedly strengthened in the acRG-high group. We developed and confirmed an excellent acRG-related signature (acRGS) utilizing a comprehensive set of 101 algorithm combinations derived from 10 machine learning algorithms. Hereby, the acRGS, including MYO10, ZNF667, MRAS, SCO2, MAPK10, PNMA6A, KPNA2, NT5DC2, BAIAP2L2 and NDST3, delineated ac4C-associated mRNA modification patterns in melanoma. The acRGS possesses distinctly superior performance to 120 previously reported signatures in melanoma and could predict the overall survival of melanoma patients across four external datasets. The substantial associations among immune checkpoint genes, immune cell infiltration, and tumor mutation burden with acRGS indicate that acRGS is helpful in identifying melanoma patients who are sensitive to immunotherapy. Besides, we confirmed that MYO10 was mainly overexpressed in melanoma tissues, and elevated MYO10 was positively correlated with malignant phenotypes and unfavorable prognosis in melanoma patients. Silencing MYO10 expression inhibited melanoma cell proliferation, migration and invasion in vitro as well as tumor growth in vivo. Taken together, the acRGS could function as a reliable and prospective tool to improve the clinical prognosis for melanoma individuals.

Integrated single-cell analysis reveals the regulatory network of disulfidptosis-related lncRNAs in bladder cancer: constructing a prognostic model and predicting treatment response

Background

Disulfidptosis is a newly discovered form of cell death, and long non-coding RNAs (lncRNAs) play a crucial role in tumor cell growth, migration, recurrence, and drug resistance, particularly in bladder cancer (BLCA). This study aims to investigate disulfidptosis-related lncRNAs (DRLs) as potential prognostic markers for BLCA patients.

Methods

Utilizing single-cell sequencing data, RNA sequencing data, and corresponding clinical information sourced from the GEO and TCGA databases, this study conducted cell annotation and intercellular communication analyses to identify differentially expressed disulfide death-related genes (DRGs). Subsequently, Pearson correlation and Cox regression analyses were employed to discern DRLs that correlate with overall survival. A prognostic model was constructed through LASSO regression analysis based on DRLs, complemented by multivariate Cox regression analysis. The performance of this model was rigorously evaluated using Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and area under the ROC curve (AUC). Furthermore, this investigation delved into the potential signaling pathways, immune status, tumor mutation burden (TMB), and responses to anticancer therapies associated with varying prognoses in patients with BLCA.

Results

We identified twelve differentially expressed DRGs and elucidated their corresponding intercellular communication relationships. Notably, epithelial cells function as ligands, signaling to other cell types, with the interactions between epithelial cells and both monocytes and endothelial cells exhibiting the strongest connectivity. This study identified six DRLs in BLCA-namely, C1RL-AS1, GK-AS1, AC134349.1, AC104785.1, AC011092.3, and AC009951.6, and constructed a nomogram to improve the predictive accuracy of the model. The DRL features demonstrated significant associations with various clinical variables, diverse immune landscapes, and drug sensitivity profiles in BLCA patients. Furthermore, RT-qPCR validation confirmed the aberrant expression levels of these DRLs in BLCA tissues, affirming the potential of DRL characteristics as prognostic biomarkers.

Conclusion

We established a DRLs model that serves as a predictive tool for the prognosis of BLCA patients, as well as for assessing tumor mutation burden, immune cell infiltration, and responses to immunotherapy and targeted therapies. Collectively, this study contributes valuable insights toward advancing precision medicine within the context of BLCA.

Revolutionary Cancer Therapy for Personalization and Improved Efficacy: Strategies to Overcome Resistance to Immune Checkpoint Inhibitor Therapy

Cancer remains a significant public health issue worldwide, standing as a primary contributor to global mortality, accounting for approximately 10 million fatalities in 2020 [...].

Machine learning identifies clinical tumor mutation landscape pathways of resistance to checkpoint inhibitor therapy in NSCLC

BACKGROUND

Immune checkpoint inhibitors (CPIs) have revolutionized cancer therapy for several tumor indications. However, a substantial fraction of patients treated with CPIs derive no benefit or have short-lived responses to CPI therapy. Identifying patients who are most likely to benefit from CPIs and deciphering resistance mechanisms is therefore essential for developing adjunct treatments that can abrogate tumor resistance.

PATIENTS AND METHODS

In this study, we used a machine learning approach that used the US-based nationwide de-identified Flatiron Health and Foundation Medicine non-small cell lung carcinoma (NSCLC) clinico-genomic database to identify genomic markers that predict clinical responses to CPI therapy. In total, we analyzed data from 4,433 patients with NSCLC.

RESULTS

Analysis of pretreatment genomic data from 1,511 patients with NSCLC identified. Of the 36 genomic signatures identified, 33 exhibited strong predictive capacity for CPI response (n=1150) compared with chemotherapy response (n=361), while three signatures were prognostic. These 36 genetic signatures had in common a core set of four genes (BRAF, BRIP1, FGF10, and FLT1). Interestingly, we observed that some (n=19) of the genes in the signatures (eg, TP53, EZH2, KEAP1 and FGFR2) had alternative mutations with contrasting clinical outcomes to CPI therapy. Finally, the genetic signatures revealed multiple biological pathways involved in CPI response, including MAPK, PDGF, IL-6 and EGFR signaling.

CONCLUSIONS

In summary, we found several genomic markers and pathways that provide insight into biological mechanisms affecting response to CPI therapy. The analyses identified novel targets and biomarkers that have the potential to provide candidates for combination therapies or patient enrichment strategies, which could increase response rates to CPI therapy in patients with NSCLC.

Individualized Neoantigen-Directed Melanoma Therapy

Individualized neoantigen-directed therapy represents a groundbreaking approach in melanoma treatment that leverages the patient's own immune system to target cancer cells. This innovative strategy involves the identification of unique immunogenic neoantigens (mutated proteins specific to an individual's tumor) and the development of therapeutic vaccines that either consist of peptide sequences or RNA encoding these neoantigens. The goal of these therapies is to induce neoantigen-specific immune responses, enabling the immune system to recognize and destroy cancer cells presenting the targeted neoantigens. This individualized approach is particularly advantageous given the genetic heterogeneity of melanoma, which exhibits distinct mutations among different patients. In contrast to traditional therapies, neoantigen-directed therapy offers a tailored treatment that potentially reduces off-target side effects and enhances therapeutic efficacy. Recent advances in neoantigen prediction and vaccine development have facilitated clinical trials exploring the combination of neoantigen vaccines with immune checkpoint inhibitors. These trials have shown promising clinical outcomes, underscoring the potential of this personalized approach. This review provides an overview of the rationale behind neoantigen-directed therapies and summarizes the current state of knowledge regarding personalized neoantigen vaccines in melanoma treatment.

Pretrained transformers applied to clinical studies improve predictions of treatment efficacy and associated biomarkers

Cancer treatment has made significant advancements in recent decades, however many patients still experience treatment failure or resistance. Attempts to identify determinants of response have been hampered by a lack of tools that simultaneously accommodate smaller datasets, sparse or missing measurements, multimodal clinicogenomic data, and that can be interpreted to extract biological or clinical insights. We introduce the Clinical Transformer, an explainable transformer-based deep-learning framework that addresses these challenges. Our framework maximizes data via self-supervised, gradual, and transfer learning, and yields survival predictions surpassing performance of state-of-the-art methods across diverse, independent datasets. The framework's generative capability enables in silico perturbation experiments to test counterfactual hypotheses. By perturbing immune-associated features in immunotherapy-naive patients, we identify a patient subset that may benefit from immunotherapy, and we validate this finding across three independent immunotherapy-treated cohorts. We anticipate our work will empower the scientific community to further harness data for the benefit of patients.

Modeling and simulation of genotypic Tumor Mutational Burden and Phenotypic Immunogenicity biomarkers in cancer immunoediting with Ising-Hamiltonian characterization

BACKGROUND AND OBJECTIVE

In the Tumor Micro-Environment, cancer progression and its relationship with the Immune System (IS) are described in terms of cancer immunoediting (CI) phases, each of which is characterized by different types and levels of interaction between the tumor cells and elements of the IS, such as CD8+T cells. Said interactions are governed by genotypical (Tumor Mutational Burden, TMB) and phenotypical aspects pertaining to the tumor, as well as by the strength of the IS. In this work, a computational model of CI is presented that incorporates the TMB and the biomarker Tumor Immunogenic Phenotype (TIP) as its control parameters, and which employs the Ising-model Hamiltonian to characterize the system with respect to the CI phases.

METHODS

Our model is a probabilistic multi-agent system with agents for tumor cells and for the IS. The computer implementation includes the parametrization of the TMB and the TIP, which is useful for identifying whether a tumor is hot or cold based on tumor immunogenicity and inflammation. For modeling the interactions between tumor and immune cells, the relevant elements are integrated under a Michaelis-Menten equation that regulates the recruitment rate of CD8+T cells and other IS elements. This novel quantification of immune cell recruitment encompasses the growth of neoantigen production, which in turn triggers the growth of CD8+T cells.

RESULTS

Our model reliably captures the Elimination, Equilibrium, and Escape phases of tumor-immune cell interactions, modulating the observed behaviors through the introduced parametrization of TMB and TIP biomarkers. Notably, these results align well with the combination of genotypical and phenotypical biomarkers analyzed in recent literature. A remarkable instance is the appreciable inhibition of the tumor activity during the Escape phase, observed for phenotypically hot tumors with relatively high TMB, and pointing towards improved efficacy of the IS against such tumors. The Ising-Hamiltonian provides precise quantification of diverse tumor-immune interactions across different TMB and TIP value combinations.

CONCLUSIONS

The presented model, formed by relatively simple agents, generates emergent behaviors through which the phases of CI are identified. The flexible choice of control parameters is robust enough and provides a plausible explanation for the mechanisms through which tumors with high TMB and high immunogenicity (i.e., hot tumors) exhibit a higher probability of responding to immunotherapy treatment. Characterization via the Ising-model Hamiltonian supports this explanation by summarizing the system's dynamics, which, in turn, facilitates its analysis and methodical improvements. The complex interplay of TMB, TIP, and individual physiology is finely captured.

Platelets and megakaryocytes in cancer

Platelets have important roles in hemostasis but also actively participate in cancer metastasis and inflammatory processes. They are produced by large precursor cells, the megakaryocytes, residing mainly in the bone marrow. Clinically, elevated platelet counts and/or increased platelet-to-lymphocyte ratio are being explored as biomarkers of metastatic disease and to predict survival or response to therapy in certain cancers. Multiple mechanisms have been put forward on how platelets promote hematogenous metastasis stemming mainly from murine experimental models. Research is now beginning to explore the potential roles of megakaryocytes in solid cancer, myeloma, and lymphoma. Here, we review mechanisms on how platelets and megakaryocytes contribute to cancer progression and metastasis but also discuss potential cancer-suppressing functions mainly related to the regulation of vascular intratumor integrity. Recent developments in cancer immune checkpoint therapy are reviewed with a focus on the potential roles of platelets. Moreover, we review studies exploring platelets for targeted drug delivery systems in cancer therapy.

A mutational signature and ARID1A mutation associated with outcome in hepatocellular carcinoma

OBJECTIVE

The prognosis of hepatocellular carcinoma (HCC) is poor and there is no stable and reliable molecular biomarker for evaluation. This study attempted to find reliable prognostic markers from tumor mutational profiles.

METHODS

A total of 362 HCC samples with whole-exome sequencing were collected as discovery datasets, and 200 samples with targeted sequencing were used for validation of the relevant results. All HCC samples were obtained from previously published studies. Bayesian non-negative matrix factorization was used to extract mutational signatures, and multivariate Cox regression models were utilized to identify the prognostic role of mutational factors. Gene set enrichment analysis was employed to discover potential signaling pathways associated with specific mutational groups.

RESULTS

In the HCC discovery dataset, a total of four mutational signatures (i.e., signatures 4, 6, 16, and 22) were extracted, of which signature 16 characterized by T>C mutations was observed to be associated with favorable HCC prognosis, and this correlation was also found in the validation dataset. Further analysis showed that patients with ARID1A mutations exhibited inferior survival outcomes in both discovery and validation datasets. Mechanistic exploration revealed that the presence of signature 16 was associated with better immune infiltration and tumor immunogenicity, while patients with ARID1A mutations were away from these favorable immunological features.

CONCLUSION

By integrating somatic mutation data and clinical information of HCC, this study identified that signature 16 and ARID1A mutations were associated with better and worse outcomes respectively, providing a basis for prognosis prediction and clinical treatment strategies of HCC.

Personalized, autologous neoantigen-specific T cell therapy in metastatic melanoma: a phase 1 trial

New treatment approaches are warranted for patients with advanced melanoma refractory to immune checkpoint blockade (ICB) or BRAF-targeted therapy. We designed BNT221, a personalized, neoantigen-specific autologous T cell product derived from peripheral blood, and tested this in a 3 + 3 dose-finding study with two dose levels (DLs) in patients with locally advanced or metastatic melanoma, disease progression after ICB, measurable disease (Response Evaluation Criteria in Solid Tumors version 1.1) and, where appropriate, BRAF-targeted therapy. Primary and secondary objectives were evaluation of safety, highest tolerated dose and anti-tumor activity. We report here the non-pre-specified, final results of the completed monotherapy arm consisting of nine patients: three at DL1 (1 × 108-1 × 109 cells) and six at DL2 (2 × 109-1 × 1010 cells). Drug products (DPs) were generated for all enrolled patients. BNT221 was well tolerated across both DLs, with no dose-limiting toxicities of grade 3 or higher attributed to the T cell product observed. Specifically, no cytokine release, immune effector cell-associated neurotoxicity or macrophage activation syndromes were reported. A dose of 5.0 × 108-1.0 × 1010 cells was identified for further study conduct. Six patients showed stable disease as best overall response, and tumor reductions (≤20%) were reported for four of these patients. In exploratory analyses, multiple mutant-specific CD4+ and CD8+ T cell responses were generated in each DP. These were cytotoxic, polyfunctional and expressed T cell receptors with broad functional avidities. Neoantigen-specific clonotypes were detected after treatment in blood and tumor. Our results provide key insights into this neoantigen-specific adoptive T cell therapy and demonstrate proof of concept for this new therapeutic approach. ClinicalTrials.gov registration: NCT04625205 .

Preclinical data and design of a phase I clinical trial of neoantigen-reactive TILs for advanced epithelial or ICB-resistant solid cancers

Background

Adoptive cell therapy (ACT) of ex vivo expanded tumor-infiltrating lymphocytes (TILs) can mediate objective tumor regression in 28%-49% of metastatic melanoma patients. However, the efficacy of TIL therapy in most epithelial cancers remains limited. We present the design of a phase I clinical study that aims to assess the safety and efficacy of NEXTGEN-TIL, a TIL product selected based on ex vivo neoantigen recognition, in patients with advanced epithelial tumors and immune checkpoint blockade (ICB)-resistant solid tumors.

Materials and methods

Pre-rapid expansion protocol (REP) TIL cultures expanded in high-dose interleukin 2 (HD-IL-2) from patients with metastatic solid tumors were screened for recognition of autologous tumor cell lines (TCLs) and/or neoantigens. Six good manufacturing practice (GMP)-grade validations of pre-REP TIL expansion were carried out and TIL cultures from these six intermediate products were selected to carry out the clinical-scale GMP validation of the REP.

Results

TILs expanded in 82% of patient-derived tumor biopsies across different cancer types and these frequently contained tumor- and neoantigen-reactive T cells. During GMP validations, a variable number of TIL cultures expanded, constituting the intermediate products (pre-REP). Three finished products were manufactured using a REP which reached cell doses ranging from 4.3e9 to 1.1e11 and met the established specifications. The NEXTGEN-TIL clinical trial entails a first expansion of TILs from tumor fragments in HD-IL-2 followed by TIL screening for neoantigen recognition and REP of selected neoantigen-reactive TIL cultures. Treatment involves a classical non-myeloablative lymphodepleting chemotherapy followed by NEXTGEN-TIL product administration together with HD-IL-2.

Conclusions

NEXTGEN-TIL exploits ex vivo expanded neoantigen-reactive TIL to potentially improve efficacy in patients with epithelial and ICB-resistant tumors, with a safety profile like traditional TILs.

T cells in the microenvironment of solid pediatric tumors: the case of neuroblastoma

Neuroblastoma (NB) is an immunologically "cold" tumor with poor or no inflamed substrates as most of solid pediatric tumors (SPT). Consistent data indicate that NB tumor microenvironment (TME) is dominated by myeloid cells, with little (but variable) T cell infiltration. The obstacles to lymphocyte infiltration and to their anti-tumor activity are due to different tumor immune evasion strategies, including loss of HLA Class I molecules, high expression of immune checkpoint molecular ligands leading to exhaustion of T effector (and NK) cells, induction of T regulatory, myeloid and stromal cells and secretion of immunosuppressive mediators. In odds with adult solid tumors, NB displays weak immunogenicity caused by intrinsic low mutational burden and scant expression of neoepitopes in the context of MHC-class I antigens which, in turn, are particularly poorly expressed on NB cells, thus inducing low anti-tumor T cell responses. In addition, NB is generated from embryonal cells and is the result of transcriptional abnormalities and not of the accumulation of genetic mutations over time, thus further explaining the low immunogenicity. The poor expression of immunogenic molecules on tumor cells is associated with the high production of immunosuppressive factors which further downregulate lymphocyte infiltration and activity, thus explaining the limited efficacy of new drugs in NB, as immune checkpoint inhibitors. This review is focused on examining the role of T effector and regulatory cells infiltrating TME of NB, taking into account their repertoire, phenotype, function, plasticity and, importantly, predictive value for defining novel targets for therapy.

Pan-cancer analysis to character the clinicopathological and genomic features of KRAS-mutated patients in China

PURPOSE

The Kirsten rat sarcoma viral oncogene (KRAS) is the most frequently mutated oncogene in human cancers. Significant advancements have been made in targeted therapy and immunotherapy for this gene in recent years, underscoring the importance of comprehensively understanding the genomic landscape of KRAS across various cancer types.

METHODS

Using next-generation sequencing (NGS) technology and a panel of 520 genes, KRAS mutations, tumor mutation burden (TMB), and microsatellite instability (MSI-H) status were investigated.

RESULTS

An analysis of 10,820 tumor samples found KRAS mutations in 19.97% of cases. Pancreatic cancer showed the highest prevalence of KRAS mutations at 73.51%, while colorectal at 41.45%, uterine at 21.23%, and lung cancer at 11.24%. KRAS G12D mutation is most common in pancreatic, colorectal, and gastric cancers, while KRAS G12V mutation is predominant in uterine cancer, and KRAS G12C mutation is most frequent in lung cancer. Significant correlations were found between TMB and KRAS G13D/G12V mutations in colorectal cancer. KRAS G13D notably affected TMB in uterus cancer, while KRAS G12C mutation was linked to high TMB in lung cancer. Moreover, statistical analysis revealed a significant association between KRAS G13D/G12V mutations and MSI-H in colorectal cancer.

CONCLUSIONS

KRAS mutations were most frequent in cancers of the digestive, female reproductive, and respiratory systems. Specific KRAS mutations are associated with TMB and MSI in various cancer types.

Comprehensive genetic variant analysis reveals combination of KRAS and LRP1B as a predictive biomarker of response to immunotherapy in patients with non-small cell lung cancer

BACKGROUND

In non-small cell lung cancer (NSCLC), the rapid advancement of predictive genetic testing of tumors by identifying specific pathogenic driver variants has significantly improved treatment guidance. However, immune checkpoint blockade (ICB) is typically administered to patients with tumors in the absence of such driver variants. Since only about 30% of patients will respond to ICB treatment, identifying novel genetic biomarkers of clinical response is crucial and will improve treatment decisions. This prospective clinical study aims to combine molecular biology, advanced bioinformatics and clinical data on response to treatment with ICB from a prospective cohort of NSCLC patients to identify single or combination of genetic variants in the tumor that can serve as predictive biomarkers of clinical response.

METHODS

In this prospective bi-center clinical study, we performed next-generation sequencing (NGS) of 597 cancer-associated genes in a prospective cohort of 49 patients as the final cohort analyzed, with stage III or IV NSCLC, followed by establishment of an in-house developed bioinformatics-based molecular classification method that integrates, interprets and evaluates data from multiple databases and variant prediction tools. Overall survival (OS) and progression-free survival (PFS) were analyzed for selected candidate genes and variants identified using our novel methodology including molecular tools, databases and clinical information.

RESULTS

Our novel molecular interpretation and classification method identified high impact variants in frequently altered genes KRAS, LRP1B, and TP53. Analysis of these genes as single predictive biomarkers in ICB-treated patients revealed that the presence of likely pathogenic variants and variants of unclear significance in LRP1B was associated with improved OS (p = 0.041). Importantly, further analysis of variant combinations in the tumor showed that co-occurrence of KRAS and LRP1B variants significantly improved OS (p = 0.003) and merged PFS (p = 0.008). Notably, the triple combination of variants in KRAS, LRP1B, and TP53 positively impacted both OS (p = 0.026) and merged PFS (p = 0.003).

CONCLUSIONS

This study suggests that combination of the LRP1B and KRAS variants identified through our novel molecular classification scheme leads to better outcomes following ICB treatment in NSCLC. The addition of TP53 improves the outcome even further. To our knowledge, this is the first report indicating that harboring a combination of KRAS, LRP1B, and TP53 variants can significantly enhance the response to ICB, suggesting a novel predictive biomarker combination for NSCLC patients.

Mismatch repair (MMR) and microsatellite instability (MSI) phenotypes across solid tumors: A comprehensive cBioPortal study on prevalence and prognostic impact

Mismatch repair deficiency (MMR-d) and microsatellite instability (MSI) are prognostic and predictive biomarkers in oncology. Current testing for MMR/MSI relies on immunohistochemistry (IHC) for MMR proteins and molecular assays for MSI detection. This combined diagnostic strategy, however, lacks tumor specificity and does not account for gene variants. This study provides an in-depth analysis of MMR mutations frequency, spectrum, and distribution in solid tumors. Data from 23,893 patients across 11 tumor types, using 66 publicly available studies, were analyzed. MMR-mutated (MMR-m) status was defined by alterations in MLH1, PMS2, MSH2, and/or MSH6; MSI was assessed by MSIsensor. Cases with indeterminate labelling were excluded. Survival was analyzed using the Kaplan-Meier method. Among 19,353 tumors, 949 MMR variants were identified, comprising 432 pathogenic and 517 variants of unknown significance (VUS), as defined by OncoKB. MSH6 mutations were the most frequent (n = 279, 29.4 %), followed by MSH2 (n = 198, 20.9 %), MLH1 (n = 187, 19.7 %), and PMS2 (n = 161, 16.9 %). MMR-m cases were more frequent in endometrial (EC, 20.5 %), colorectal (CRC, 8.2 %), bladder (BLCA, 8.7 %), and gastroesophageal cancers (GEC, 5.4 %). Pathogenic mutations were more common than non-pathogenic in EC, CRC, and GEC (p < 0.001, p = 0.01, p = 0.32, respectively). MMR-m status was not associated with MSI in 247 (48.9 %) cases, including 67 (13.2 %) with pathogenic mutations. The highest concordance between MMR-m and MSI was observed in CRC (65.7 %), EC (91.2 %), and GEC (69.6 %), while the lowest in pancreatic (0.2 %) and lung cancers (0.1 %). MMR-m GECs showed improved overall survival compared to MMR-wt (p = 0.009), a relationship not observed in other tumor types. This study demonstrates that the MMR spectrum is extremely hetoerogeneous in solid tumors, highliting the need for comprehensive and tumor-specific testing strategies.

Clinical metric of tumor mutational burden depicts colorectal cancer patients at the extremes

PURPOSE

Rare cases of colorectal cancer patients with exceptionally good or poor prognosis often remain overlooked, limiting insights into prognostic factors and underlying mechanisms.

METHODS

This study developed an analytical framework to investigate cancer patients at the extremes using tumor mutational burden (TMB). By analyzing data from 1277 colorectal cancer patients who did not receive immunotherapy, this analysis assessed how patient survival varies with a broad range of TMB levels.

RESULTS

Among patients with TMB ≤ 10 mutations per megabase (mut/Mb), increasing TMB was associated with worse survival outcomes. In contrast, patients with TMB > 10 mut/Mb showed  increasingly improved survival. Notably, a small subgroup (3.83%) with TMB > 60 mut/Mb had significantly better survival outcomes.

CONCLUSIONS

These findings highlight TMB's dual role in colorectal cancer progression. This study suggests that atypical patients can coexist within the same "disease continuum" with typical patients, under the universal context unified by a shared cancer hallmark. TMB provides a useful biomarker for identifying these extremes, offering a clinical metric to better predict patient outcomes and personalize treatment strategies.

Comprehensive Survey of AACR GENIE Database of Tumor Mutation Burden (TMB) Among All Three Classes (I, II, III) of BRAF Mutated (BRAF+) NSCLC

Background

BRAF mutations are generally divided into three classes based on the different altered mechanism of activation.

Methods

We queried the public AACR GENIE database (version 13.1), which includes tumor mutation burden (TMB) data, to explore potential molecular differences among the three classes of non-small cell lung cancer (NSCLC).

Results

Out of 20,713 unique NSCLC patients, 324 (1.6%) were BRAF mutations positive (BRAF+) class I, 260 (1.3%) class II, and 236 (1.1%) class III. The distribution of patient characteristics, including sex, age, and race, remains uniform across the three classes. The median TMB (mt/MB) was 6.5, 9.5, and 10.3 for class I, II, and III, respectively. The mean TMB was 61.5 ± 366.1 for class I, 40.5 ± 156.2 for class II, and 129.4 ± 914.8 for class III. About 30.5% of BRAF V600E+ patients had TMB ≥ 10; 47.7% of class II had TMB ≥ 10; and 52.5% of class III had TMB ≥ 10. For those patients with TMB ≥ 10, the median TMB was 45, 28.9, 18.4 for class I, II, and III, respectively. For TMB ≥ 10 patients, TP53 mutation was the most common co-alterations across all 3 classes.

Conclusion

A substantial proportion of BRAF+ NSCLC patients exhibited a TMB ≥ 10, among all three classes of BRAF mutation classification, including BRAF V600E+ NSCLC. Class III mutations appeared to have the highest median TMB, followed by class II, and then class I.

Comprehensive single-cell analysis of triple-negative breast cancer based on cDC1 immune-related genes: prognostic model construction and immunotherapy potential

BACKGROUND

Various components of the immunological milieu surrounding tumors have become a key focus in cancer immunotherapy research. There are currently no reliable biomarkers for triple-negative breast cancer (TNBC), leading to limited clinical benefits. However, some studies have indicated that patients with TNBC may achieve better outcomes after immunotherapy. Therefore, this study aimed to identify molecular features potentially associated with conventional type 1 dendritic cell (cDC1) immunity to provide new insights into TNBC prognostication and immunotherapy decision-making.

METHODS

Single-cell ribonucleic acid sequencing data from the Gene Expression Omnibus database were analyzed to determine which genes are differentially expressed genes (DEGs) in cDC1s. We then cross-referenced cDC1-related DEGs with gene sets linked to immunity from the ImmPort and InnateDB databases to screen for the genes linked to the immune response and cDC1s. We used univariate Cox and least absolute shrinkage and selection operator regression analyses to construct a risk assessment model based on four genes in patients with TNBC obtained from the Cancer Genome Atlas, which was validated in a testing group. This model was also used to assess immunotherapy responses among the IMvigor210 cohort. We subsequently utilized single sample Gene Set Enrichment Analysis, CIBERSORT, and ESTIMATE to analyze the immunological characteristics of the feature genes and their correlation with drug response.

RESULTS

We identified 93 DEGs related to the immune response and cDC1s, of which four (IDO1, HLA-DOB, CTSD, and IL3RA) were substantially linked to the overall survival rate of TNBC patients. The risk assessment model based on these genes stratified patients into high- and low-risk groups. Low-risk patients exhibited enriched ''hot tumor'' phenotypes, including higher infiltration of memory-activated CD4 + T cells, CD8 + T cells, gamma delta T cells, and M1 macrophages, as well as elevated immune checkpoint expression and tumor mutational burden, suggesting potential responsiveness to immunotherapy. Conversely, high-risk patients displayed "cold tumor" characteristics, with higher infiltration of M0 and M2 macrophages and lower immune scores, which may be poorer in response to immunotherapy. However, experimental validation and larger clinical studies are necessary to confirm these findings and explore the underlying mechanisms of the identified genes.

CONCLUSION

This study developed a robust risk assessment model using four genes that effectively forecast the outcome of patients with TNBC and have the potential to guide immunotherapy. This model provided new theoretical insights for knowing the TNBC immune microenvironment and developing personalized treatment strategies.

Cancer vaccines: current status and future directions

Cancer continues to be a major global health burden, with high morbidity and mortality. Building on the success of immune checkpoint inhibitors and adoptive cellular therapy, cancer vaccines have garnered significant interest, but their clinical success remains modest. Benefiting from advancements in technology, many meticulously designed cancer vaccines have shown promise, warranting further investigations to reach their full potential. Cancer vaccines hold unique benefits, particularly for patients resistant to other therapies, and they offer the ability to initiate broad and durable T cell responses. In this review, we highlight the antigen selection for cancer vaccines, introduce the immune responses induced by vaccines, and propose strategies to enhance vaccine immunogenicity. Furthermore, we summarize key features and notable clinical advances of various vaccine platforms. Lastly, we delve into the mechanisms of tumor resistance and explore the potential benefits of combining cancer vaccines with standard treatments and other immunomodulatory approaches to improve vaccine efficacy.

Identification of nonsense-mediated decay inhibitors that alter the tumor immune landscape

Despite exciting developments in cancer immunotherapy, its broad application is limited by the paucity of targetable antigens on the tumor cell surface. As an intrinsic cellular pathway, nonsense-mediated decay (NMD) conceals neoantigens through the destruction of the RNA products from genes harboring truncating mutations. We developed and conducted a high-throughput screen, based on the ratiometric analysis of transcripts, to identify critical mediators of NMD in human cells. This screen implicated disruption of kinase SMG1's phosphorylation of UPF1 as a potential disruptor of NMD. This led us to design a novel SMG1 inhibitor, KVS0001, that elevates the expression of transcripts and proteins resulting from human and murine truncating mutations in vitro and murine cells in vivo. Most importantly, KVS0001 concomitantly increased the presentation of immune-targetable human leukocyte antigens (HLA) class I-associated peptides from NMD-downregulated proteins on the surface of human cancer cells. KVS0001 provides new opportunities for studying NMD and the diseases in which NMD plays a role, including cancer and inherited diseases.

Durable Response of Pembrolizumab for EGFR Mutation-positive Lung Adenocarcinoma with Early Progression to Osimertinib in First-line Treatment

Osimertinib, a third-generation epidermal growth factor receptor tyrosine kinase inhibitor, is the standard first-line treatment for EGFR mutation-positive non-small-cell lung cancer (NSCLC) and demonstrates favorable disease control. Conversely, immune checkpoint inhibitors (ICIs) that target programmed cell death-1/programmed cell death ligands demonstrate a restrictive tumor response. We herein report a patient who achieved a durable response to pembrolizumab following early progression within two months of osimertinib administration for EGFR mutation-positive lung adenocarcinoma. Our findings suggest that treatment with ICIs for patients with EGFR mutation-positive NSCLC experiencing early progression to osimertinib as first-line treatment might represent a viable approach.

Mechanisms of Resistance to Anti-PD-1 Immunotherapy in Melanoma and Strategies to Overcome It

Resistance to anti-PD-1 therapy in melanoma remains a major obstacle in achieving effective and durable treatment outcomes, highlighting the need to understand and address the underlying mechanisms. The first key factor is innate anti-PD-1 resistance signature (IPRES), an expression of a group of genes associated with tumor plasticity and immune evasion. IPRES promotes epithelial-to-mesenchymal transition (EMT), increasing melanoma cells' invasiveness and survival. Overexpressed AXL, TWIST2, and WNT5a induce phenotypic changes. The upregulation of pro-inflammatory cytokines frequently coincides with EMT-related changes, further promoting a resistant and aggressive tumor phenotype. Inflamed tumor microenvironment may also drive the expression of resistance. The complexity of immune resistance development suggests that combination therapies are necessary to overcome it. Furthermore, targeting epigenetic regulation and exploring novel approaches such as miR-146a modulation may provide new strategies to counter resistance in melanoma.

Unveiling the prognostic significance of RNA editing-related genes in colon cancer: evidence from bioinformatics and experiment

BACKGROUND

RNA editing is recognized as a crucial factor in cancer biology. Its potential application in predicting the prognosis of colon adenocarcinoma (COAD) remains unexplored.

METHODS

RNA editing data of COAD patients were downloaded from the Synapse database. LASSO regression was used to construct the risk model and verified by the receiver operating characteristic (ROC) curve. GO and KEGG enrichment analyses were performed to delineate the biological significance of the differentially expressed genes. Finally, differential analysis and immunohistochemistry were used to verify the expression of adenosine deaminase 1 (ADAR1).

RESULTS

We evaluated a total of 4079 RNA editing sites in 514 COAD patients from Synapse database. A prognostic signature was constructed based on five genes were significantly associated with the prognosis of COAD patients including GNL3L, NUP43, MAGT1, EMP2, and ARSD. Univariate and multivariate Cox regression analysis revealed that RNA editing-related genes (RERGs)-related signature was an independent risk factor for COAD. Moreover, Experimental evidence shows that ADAR1 is highly expressed in colon adenocarcinoma and silencing ADAR1 can inhibit cancer cell proliferation.

CONCLUSION

We established a prognostic model based on five RERGs with strong predictive value. This model not only serves as a foundation for a novel prognostic tool but also facilitates the identification of potential drug candidates for treating COAD.

Mechanisms of T-cell Depletion in Tumors and Advances in Clinical Research

T lymphocytes (T cells) are essential components of the adaptive immune system that play a vital role in identifying and eliminating infected and tumor cells. In tumor immunotherapy, T cells have emerged as a promising therapeutic strategy due to their high specificity, potent cytotoxic capability, long-lasting immune memory, and adaptability within immunotherapeutic approaches. However, tumors can evade the immune system by depleting T cells through various mechanisms, such as inhibitory receptor signaling, metabolic exhaustion, and physical barriers within the tumor microenvironment. This review provided an overview of the mechanisms underlying T-cell depletion in tumors and discussed recent advances in clinical research related to T-cell immunotherapy for tumors. It highlighted the need for in-depth studies on key issues such as indications, dosage, and sequencing of combined therapeutic strategies tailored to different patients and tumor types, providing practical guidance for individualized treatment. Future research on T-cell depletion would be necessary to uncover the fundamental mechanisms and laws of T-cell depletion, offering both theoretical insights and practical guidance for the selection and optimization of tumor immunotherapy. Furthermore, interdisciplinary, cross-disciplinary, and international collaborative innovations are necessary for developing more effective and safer treatments for tumor patients.

CBX2 suppresses interferon signaling to diminish tumor immunogenicity via a noncanonical corepressor complex

Chromobox 2 (CBX2), a crucial component of the polycomb repressive complex (PRC), has been implicated in the development of various human cancers. However, its role in the regulation of tumor immunogenicity and immune evasion remains inadequately understood. In this study, we found that ablation of CBX2 led to tumor growth inhibition, activation of the tumor immune microenvironment, and enhanced therapeutic efficacy of anti-PD1 or adoptive T cell therapies by using murine syngeneic tumor models. By analysis of the CBX2-regulated transcriptional program coupled with mass spectrometry screening of CBX2-interacting proteins, we found that CBX2 suppresses interferon signaling independent of its function in the canonical PRC. Mechanistically, CBX2 directly interacts with RACK1 and facilitates the recruitment of HDAC1, which attenuates the H3K27ac modification on the promoter regions of interferon-stimulated genes, thereby suppressing interferon signaling. Consequently, CBX2 reduces tumor immunogenicity and enables immune evasion. Moreover, a high expression level of CBX2 is associated with immune suppressive tumor microenvironment and reduced efficacy of immunotherapy across various human cancer types. Our study identifies a noncanonical CBX2-RACK1-HDAC1 corepressor complex in suppression of tumor immunogenicity, thereby presenting a potential target and biomarker for tumor immunotherapy.

Identification and Phenotypic Characterization of Neoantigen-Specific Cytotoxic CD4+ T Cells in Endometrial Cancer

Tumor-reactive CD4+ T cells often accumulate in the tumor microenvironment (TME) in human cancer, but their functions and roles in antitumor responses remain elusive. Here, we investigated the immunopeptidome of HLA class II-positive (HLA-II+) endometrial cancer with an inflamed TME using a proteogenomic approach. We identified HLA-II neoantigens, one of which induced polyclonal CD4+ tumor-infiltrating lymphocyte responses. We then experimentally demonstrated that neoantigen-specific CD4+ tumor-infiltrating lymphocytes lyse target cells in an HLA-II-dependent manner. Single-cell transcriptomic analysis of the TME coupled with T-cell receptor sequencing revealed the presence of CD4+ T-cell clusters characterized by CXCL13 expression. The CXCL13+ clusters contained two subclusters with distinct cytotoxic gene expression patterns. The identified neoantigen-specific CD4+ T cells were found exclusively in one of the CXCL13+ subclusters characterized by granzyme B and CCL5 expression. These results demonstrate the involvement of tumor-reactive CD4+ T cells with cytotoxic function in immune surveillance of endometrial cancer and reveal their transcriptomic signature.

Tumor mutational burden: why is it still a controversial agnostic immunotherapy biomarker?

For the past few years, researchers and oncologists have been pushing to find biomarkers that would help predict which treatment option would best work on a patient. Tumor Mutational Burden (TMB) is one of the latest biomarkers that is being studied and considered as a promising agnostic immunotherapy biomarker. However, it still shows controversial results in studies due to the difficulty in finding solid comparable results. This is a consequence of different cutoff definitions among many cancer types, age ranges, and the use of different sequencing assays, in addition to its association with other biomarkers such as PD-L1. Finally, the use of composite biomarkers to assess the genetic signature of a tumor might be the way forward to seriously use TMB as an agnostic biomarker.

Discovery of tumor-reactive T cell receptors by massively parallel library synthesis and screening

T cell receptor (TCR) gene therapy is a potent form of cellular immunotherapy in which patient T cells are genetically engineered to express TCRs with defined tumor reactivity. However, the isolation of therapeutic TCRs is complicated by both the general scarcity of tumor-specific T cells among patient T cell repertoires and the patient-specific nature of T cell epitopes expressed on tumors. Here we describe a high-throughput, personalized TCR discovery pipeline that enables the assembly of complex synthetic TCR libraries in a one-pot reaction, followed by pooled expression in reporter T cells and functional genetic screening against patient-derived tumor or antigen-presenting cells. We applied the method to screen thousands of tumor-infiltrating lymphocyte (TIL)-derived TCRs from multiple patients and identified dozens of CD4+ and CD8+ T-cell-derived TCRs with potent tumor reactivity, including TCRs that recognized patient-specific neoantigens.

Evaluating Tumour Mutational Burden as a Key Biomarker in Personalized Cancer Immunotherapy: A Pan-Cancer Systematic Review

BACKGROUND

Tumour mutational burden (TMB) is an emerging biomarker for predicting the efficacy of immune checkpoint inhibitors (ICIs) in cancer therapy. While its role is well established in lung cancer and melanoma, its predictive value for breast and prostate cancers remains unclear.

OBJECTIVE

This systematic review aimed to assess the predictive value of TMB for ICI therapy across four major cancer types-lung, melanoma, breast, and prostate-and to explore factors contributing to the variability in its effectiveness as a biomarker.

METHODS

A systematic search and a review of the literature were conducted in accordance with PRISMA guidelines. Studies examining the relationship between TMB levels and clinical outcomes following ICI therapy in the specified cancers were analyzed. The data were synthesized to evaluate TMB's predictive value and identify gaps in the current research.

RESULTS

High TMB consistently correlated with improved outcomes in lung cancer and melanoma, confirming its predictive utility in these cancers. Conversely, the findings for breast and prostate cancers were inconclusive. The variability in TMB's predictive value for these cancers suggests the need for complementary biomarkers or refined criteria to enhance its reliability. Methodological inconsistencies in TMB evaluation were also noted as a significant limitation.

CONCLUSIONS

TMB serves as a robust biomarker for predicting ICI response in lung cancer and melanoma, but demonstrates limited predictive utility in breast and prostate cancers. Future research should prioritize standardizing TMB assessment protocols and investigating additional biomarkers to improve treatment personalization for these cancer types.

Immune checkpoint inhibitors plus taxane-based chemotherapy for patients with advanced/metastatic NSCLC: a systematic review and meta-analysis across different PD-L1 expression levels

BACKGROUND

Immune checkpoint inhibitors (ICIs) are currently the primary approach for managing NSCLC. However, numerous combination therapies are currently under investigation. Our goal is to investigate the overall efficacy and safety of ICIs and taxane-based chemotherapy.

METHODS

We conducted a systematic review and meta-analysis, searching web databases for relevant literature. We limited our eligibility to phase II/III randomized clinical trials involving advanced/metastatic NSCLC patients.

RESULTS

We performed a meta-analysis encompassing nineteen studies derived from sixteen RCTs. For patients with sq-NSCLC PD-L1 ≥ 50%, using ICIs plus taxane significantly improve PFS and OS with HR of 0.58 (95% CI, 0.45-0.74, p < 0.0001) and 0.41 (95% CI, 0.33-0.50, p < 0.00001), respectively. For patients with non-sq NSCLC PD-L1 1-49%, the analysis revealed significant improvement of OS and PFS with HR of 0.64 (95% CI, 0.47-0.88, p = 0.005) and 0.62 (95% CI, 0.47-0.81, p = 0.0004), respectively. For TRAEs of all grades, ICIs plus taxane resulted with no significant difference compared to control group with risk ratio (RR) 1.00 (95% CI 0.99-1.02).

CONCLUSION

The analysis revealed significant improvement in efficacy of ICIs with taxane in advanced/metastatic NSCLC patients compared with ICI/taxane monotherapy.Registration: PROSPERO (CRD42023447532).

CAR-engineered NK cells versus CAR T cells in treatment of glioblastoma; strength and flaws

Glioblastoma (GBM) is a highly aggressive primary brain tumor that carries a grim prognosis. Because of the dearth of treatment options available for treatment of GBM, Chimeric Antigen Receptor (CAR)-engineered T cell and Natural Killer (NK) therapy could provide alternative strategies to address the challenges in GBM treatment. In these approaches, CAR T and NK cells are engineered for cancer-specific immunotherapy by recognizing surface antigens independently of major histocompatibility complex (MHC) molecules. However, the efficacy of CAR T cells is hindered by GBM's downregulation of its targeted antigens. CAR NK cells face similar challenges, but, in contrast, they offer advantages as off-the-shelf allogeneic products, devoid of graft-versus-host disease (GVHD) risk as well as anti-cancer activity beyond CAR specificity, potentially reducing the risk of relapse or resistance. Despite CAR T cell therapies being extensively studied in clinical settings, the use of CAR-modified NK cells in GBM treatment remains largely in the preclinical stage. This review aims to discuss recent advancements in NK cell and CAR T cell therapies for GBM, including methods for introducing CARs into both NK cells and T cells, addressing manufacturing challenges, and providing evidence supporting the efficacy of these approaches from preclinical and early-phase clinical studies. The comprehensive evaluation of CAR-engineered NK cells and CAR T cells seeks to identify the optimal therapeutic approach for GBM, contributing to the development of effective immunotherapies for this devastating disease.

Survival outcomes and response rates among patients with recurrent or metastatic head and neck squamous cell carcinoma

Evaluation of survival outcomes and response rates among patients with recurrent or metastatic head and neck squamous cell carcinoma (HNSCC) treated with checkpoint inhibitors is of interest. Data regarding overall survival (OS), progression free survival (PFS), response rate, PD-L1 combined positive score (CPS) was retrieved. A total of 412 patients with histo-pathologically confirmed recurrent or metastatic HNSCC who received checkpoint inhibitor (CPI) treatment were ultimately included as members of the cohort. The median overall survival was 13.1 months. Median PFS was 4.1 months. The estimated 1-year overall survival was 53.9% while estimated 1-year PFS was 9.7%. Thus, the use of CPI therapies for first - or second-line treatment of recurrent or metastatic head and neck squamous cell carcinoma is shown.