Genomic correlates of response to immune checkpoint blockade in microsatellite-stable solid tumors

Towards a framework for predicting immunotherapy outcome: a hybrid multiscale mathematical model of immune response to vascular tumor growth

Studying tumor immune microenvironment (TIME) is pivotal to understand the mechanism and predict the outcome of cancer immunotherapy. Systems biology mathematical models can consider and control various factors of TIME and therefore explore the anti-tumor immune response meticulously. However, the role of tumor vasculature in the recruitment of T cells and the mechanism of T cell migration through TIME have not been studied comprehensively. In this work, we developed a hybrid discrete-continuum multi-scale model to study TIME. The mathematical model includes angiogenesis and T cell recruitment via tumor vasculature. Moreover, solid tumor growth, vascular growth and remodeling, interstitial fluid flow, hemodynamics, and blood rheology are all considered in the model. In addition, different aspects of T cells, including their migration, proliferation, subtype conversion, and interaction with tumor cells are thoroughly included. The model reproduces spatiotemporal distribution of tumor infiltrating T cells that mimics histopathological patterns. Furthermore, TIME model robustly recapitulates different phases of tumor immunoediting. We also examined a number of biomarkers to predict the outcome of immune checkpoint blockade (ICB) treatment. The results demonstrated that although tumor mutational burden (TMB) may predict non-responders to ICB, a combination of different biomarkers is essential to predict the majority of the responders. Based on our results, the ICB response rate varies significantly from 28 to 89% depending on the values of different parameters, even in the cases with high TMB.

Predictive value of ZFHX4 mutation for the efficacy of immune checkpoint inhibitors in non-small cell lung cancer and melanoma

Studies have shown that the Zinc finger homeobox 4 (ZFHX4) might be a factor in the prognosis of malignancies. However, little is known about the association between the ZFHX4 mutation and the effectiveness of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer (NSCLC) and melanoma. Three public ICIs-treated NSCLC cohorts were divided into discovery cohort (n=75) and validation cohort (n=62), which were used to evaluate the relationship between ZFHX4 mutation and ICIs effectiveness in NSCLC. Seven ICIs-treated melanoma cohorts (n = 418) were used to analyze the relationship between ZFHX4 mutation and immunotherapy efficacy in melanoma. NSCLC and skin cutaneous melanoma (SKCM) cohorts from The Cancer Genome Atlas (TCGA) were used to investigate underlying mechanism. Patients with ZFHX4 mutant-type (ZFHX4-Mut) showed a superior objective response rate (ORR) (P < 0.01) and longer progression-free survival (PFS) (P < 0.05) than patients with ZFHX4 wild-type (ZFHX4-WT) in NSCLC cohorts. In the melanoma cohorts, patients carrying ZFHX4-Mut had a higher ORR (P = 0.042) and longer overall survival (OS) (P = 0.011). Besides, patients with NSCLC and melanoma harboring ZFHX4-Mut had a higher tumor mutation burden (TMB) (P<0.001) and tumor neoantigen burden (TNB) (P<0.001) than those harboring ZFHX4-WT. ZFHX4 mutation was associated with higher levels of plasma B cells, activated CD4+ memory T cells, and CD8+ T cells. Seven DNA damage repair pathways were significantly enriched in the ZFHX4-Mut group. ZFHX4 mutation could serve as a predicter for the efficacy of ICIs therapy in NSCLC and melanoma.

Tumour mutational burden: clinical utility, challenges and emerging improvements

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistent or HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

Mediating kinase activity in Ras-mutant cancer: potential for an individualised approach?

It is widely acknowledged that there is a considerable number of oncogenic mutations within the Ras superfamily of small GTPases which are the driving force behind a multitude of cancers. Ras proteins mediate a plethora of kinase pathways, including the MAPK, PI3K, and Ral pathways. Since Ras was considered undruggable until recently, pharmacological targeting of pathways downstream of Ras has been attempted to varying success, though drug resistance has often proven an issue. Nuances between kinase pathway activation in the presence of various Ras mutants are thought to contribute to the resistance, however, the reasoning behind activation of different pathways in different Ras mutational contexts is yet to be fully elucidated. Indeed, such disparities often depend on cancer type and disease progression. However, we are in a revolutionary age of Ras mutant targeted therapy, with direct-targeting KRAS-G12C inhibitors revolutionising the field and achieving FDA-approval in recent years. However, these are only beneficial in a subset of patients. Approximately 90% of Ras-mutant cancers are not KRAS-G12C mutant, and therefore raises the question as to whether other distinct amino acid substitutions within Ras may one day be targetable in a similar manner, and indeed whether better understanding of the downstream pathways these various mutants activate could further improve therapy. Here, we discuss the favouring of kinase pathways across an array of Ras-mutant oncogenic contexts and assess recent advances in pharmacological targeting of various Ras mutants. Ultimately, we will examine the utility of individualised pharmacological approaches to Ras-mediated cancer.

Antithetical impacts of deleterious LRP1B mutations in non-squamous and squamous NSCLCs on predicting benefits from immune checkpoint inhibitor alone or with chemotherapy over chemotherapy alone: retrospective analyses of the POPLAR/OAK and CHOICE-01 trials

In non-small cell lung cancers, the non-squamous and squamous subtypes (nsqNSCLC and sqNSCLC) exhibit disparities in pathophysiology, tumor immunology, and potential genomic correlates affecting responses to immune checkpoint inhibitor (ICI)-based treatments. In our in-house training cohort (n=85), the presence of the LRP1B deleterious mutation (LRP1B-del) was associated with longer and shorter progression-free survival (PFS) on ICIs alone in nsqNSCLCs and sqNSCLCs, respectively (Pinteraction=0.008). These results were validated using a larger public ICI cohort (n=208, Pinteraction<0.001). Multiplex immunofluorescence staining revealed an association between LRP1B-del and increased and decreased numbers of tumor-infiltrating CD8+ T cells in nsqNSCLCs (P=0.040) and sqNSCLCs (P=0.014), respectively. In the POPLAR/OAK cohort, nsqNSCLCs with LRP1B-del demonstrated improved PFS benefits from atezolizumab over docetaxel (hazard ratio (HR) =0.70, P=0.046), whereas this benefit was negligible in those without LRP1B-del (HR=1.05, P=0.64). Conversely, sqNSCLCs without LRP1B-del benefited more from atezolizumab (HR=0.60, P=0.002) than those with LRP1B-del (HR=1.30, P=0.31). Consistent results were observed in the in-house CHOICE-01 cohort, in which nsqNSCLCs with LRP1B-del and sqNSCLCs without LRP1B-del benefited more from toripalimab plus chemotherapy than from chemotherapy alone (Pinteraction=0.008). This multi-cohort study delineates the antithetical impacts of LRP1B-del in nsqNSCLCs and sqNSCLCs on predicting the benefits from ICI alone or with chemotherapy over chemotherapy alone. Our findings highlight the distinct clinical utility of LRP1B-del in guiding treatment choices for nsqNSCLCs and sqNSCLCs, emphasizing the necessity for a detailed analysis based on pathological subtypes when investigating biomarkers for cancer therapeutics.

Impaired TGF-β signaling via AHNAK family mutations elicits an esophageal cancer subtype with sensitivities to genotoxic therapy and immunotherapy

BACKGROUND

Genome instability (GI) is a hallmark of esophageal squamous cell carcinoma (ESCC) while factors affecting GI remain unclear.

METHODS

Here, we aimed to characterize genomic events representing specific mechanisms of GI based on 201 ESCC samples and validated our findings at the patient, single-cell and cancer cell-line levels, including a newly generated multi-omics dataset of the trial NCT04006041.

RESULTS

A two-gene (AHNAK and AHNAK2) mutation signature was identified to define the "AHNAK1/2-mutant" cancer subtype. Single-cell-assisted multi-omics analysis showed that this subtype had a higher neoantigen load, active antigen presentation, and proficient CD8 + T cell infiltrations, which were validated at pan-cancer levels. Mechanistically, AHNAK1/2-mutant ESCC was characterized by impaired response of TGF-β and the inefficient alternative end-join repair (Alt-EJ) that might promote GI. Knockdown of AHNAK in ESCC cell lines resulted in more Alt-EJ events and increased sensitivities to cisplatin. Furthermore, this two-gene signature accurately predicted better responses to DNA-damaging therapy in various clinical settings (HR ≈ 0.25). The two-gene signature predicted higher pCR rates in ESCCs receiving neoadjuvant immunotherapy-involved treatment. Finally, a molecular classification scheme was built and outperformed established molecular typing models in the prognosis stratification of ESCC patients.

CONCLUSION

Our study extended our understanding of the AHNAK family in promoting GI and selecting treatment responders of ESCC.

PTPRT loss enhances anti-PD-1 therapy efficacy by regulation of STING pathway in non-small cell lung cancer

With the revolutionary progress of immune checkpoint inhibitors (ICIs) in non-small cell lung cancer, identifying patients with cancer who would benefit from ICIs has become critical and urgent. Here, we report protein tyrosine phosphatase receptor type T (PTPRT) loss as a precise and convenient predictive marker independent of PD-L1 expression for anti-PD-1/PD-L1 axis therapy. Anti-PD-1/PD-L1 axis treatment markedly increased progression-free survival in patients with PTPRT-deficient tumors. PTPRT-deficient tumors displayed cumulative DNA damage, increased cytosolic DNA release, and higher tumor mutation burden. Moreover, the tyrosine residue 240 of STING was identified as a direct substrate of PTPRT. PTPRT loss elevated phosphorylation of STING at Y240 and thus inhibited its proteasome-mediated degradation. PTPRT-deficient tumors released more IFN-β, CCL5, and CXCL10 by activation of STING pathway and increased immune cell infiltration, especially of CD8 T cells and natural killer cells, ultimately enhancing the efficacy of anti-PD-1 therapy in multiple subcutaneous and orthotopic tumor mouse models. The response of PTPRT-deficient tumors to anti-PD-1 therapy depends on the tumor-intrinsic STING pathway. In summary, our findings reveal the mechanism of how PTPRT-deficient tumors become sensitive to anti-PD-1 therapy and highlight the biological function of PTPRT in innate immunity. Considering the prevalence of PTPRT mutations and negative expression, this study has great value for patient stratification and clinical decision-making.

A heterogeneous tumor immune microenvironment of uncommon epidermal growth factor receptor mutant non-small cell lung cancer

Common epidermal growth factor receptor (EGFR) mutations are usually not considered for immunotherapy in non-small cell lung cancer (NSCLC) due to poor efficacy. However, whether uncommon EGFR mutations are suitable for immunotherapy has not been thoroughly studied. Thus, we explored the tumor immune microenvironment (TME) features in uncommon EGFR mutant NSCLC. In this study, a total of 41 patients with EGFR mutations were included, the majority (85.4%) of whom were stage I. Among them, 22 patients harbored common mutations, while 19 patients presented with uncommon mutations. Compared with common mutations, uncommon mutations exhibited more infiltrating T cells and fewer M2 macrophages, upregulated expression of antigen processing and a presentation pathway. Unsupervised clustering based on the mIF profile identified two classes with heterogeneous TME in uncommon mutations. Class 1 featured the absence of PD-1+ cytotoxic T cell infiltration, and class 2 displayed a hotter TME because of the downregulated expression of hypoxia (p < 0.001), oxidative phosphorylation (p = 0.009), and transforming growth factor beta signaling (p = 0.01) pathways as well as increased expression of CTLA4 (p = 0.001) and PDCD1 (p = 0.004). The association of CTLA4 and PDCD1 with TME profiles was validated in a TCGA lung adenocarcinoma cohort with uncommon EGFR mutations. Our study reveals the distinct and heterogeneous TME features in uncommon EGFR mutant NSCLC.

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.

Unveiling the unique role of TSPAN7 across tumors: a pan-cancer study incorporating retrospective clinical research and bioinformatic analysis

BACKGROUND

TSPAN7 is an important factor in tumor progression. However, the precise function of TSPAN7 and its role in pan-cancer are not clear.

METHODS

Based on Xinhua cohort incorporating 370 patients with kidney neoplasm, we conducted differential expression analysis by immunohistochemistry between tumor and normal tissues, and explored correlations of TSPAN7 with patients' survival. Subsequently, we conducted a pan-cancer study, and successively employed differential expression analysis, competing endogenous RNA (ceRNA) analysis, protein-protein interaction (PPI) analysis, correlation analysis of TSPAN7 with clinical characteristics, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. Last but not least, gene set enrichment analysis was applied to identify enriched pathways of TSPAN7.

RESULTS

In Xinhua cohort, TSPAN7 expression was significantly up-regulated (P-value = 0.0019) in tumor tissues of kidney neoplasm patients. High TSPAN7 expression was associated with decreases in overall survival (OS) (P-value = 0.009) and progression-free survival (P-value = 0.009), and it was further revealed as an independent risk factor for OS (P-value = 0.0326, HR = 5.66, 95%CI = 1.155-27.8). In pan-cancer analysis, TSPAN7 expression was down-regulated in most tumors, and it was associated with patients' survival, tumor purity, tumor genomics, tumor immunity, and drug sensitivity. The ceRNA network and PPI network of TSPAN7 were also constructed. Last but not least, the top five enriched pathways of TSPAN7 in various tumors were identified.

CONCLUSION

TSPAN7 served as a promising biomarker of various tumors, especially kidney neoplasms, and it was closely associated with tumor purity, tumor genomics, tumor immunology, and drug sensitivity in pan-cancer level.

Microproteins encoded by noncanonical ORFs are a major source of tumor-specific antigens in a liver cancer patient meta-cohort

The expression of tumor-specific antigens during cancer progression can trigger an immune response against the tumor. Here, we investigate if microproteins encoded by noncanonical open reading frames (ncORFs) are a relevant source of tumor-specific antigens. We analyze RNA sequencing data from 117 hepatocellular carcinoma (HCC) tumors and matched healthy tissue together with ribosome profiling and immunopeptidomics data. Combining human leukocyte antigen-epitope binding predictions and experimental validation experiments, we conclude that around 40% of the tumor-specific antigens in HCC are likely to be derived from ncORFs, including two peptides that can trigger an immune response in humanized mice. We identify a subset of 33 tumor-specific long noncoding RNAs expressing novel cancer antigens shared by more than 10% of the HCC samples analyzed, which, when combined, cover a large proportion of the patients. The results of the study open avenues for extending the range of anticancer vaccines.

GIHP: Graph convolutional neural network based interpretable pan-specific HLA-peptide binding affinity prediction

Accurately predicting the binding affinities between Human Leukocyte Antigen (HLA) molecules and peptides is a crucial step in understanding the adaptive immune response. This knowledge can have important implications for the development of effective vaccines and the design of targeted immunotherapies. Existing sequence-based methods are insufficient to capture the structure information. Besides, the current methods lack model interpretability, which hinder revealing the key binding amino acids between the two molecules. To address these limitations, we proposed an interpretable graph convolutional neural network (GCNN) based prediction method named GIHP. Considering the size differences between HLA and short peptides, GIHP represent HLA structure as amino acid-level graph while represent peptide SMILE string as atom-level graph. For interpretation, we design a novel visual explanation method, gradient weighted activation mapping (Grad-WAM), for identifying key binding residues. GIHP achieved better prediction accuracy than state-of-the-art methods across various datasets. According to current research findings, key HLA-peptide binding residues mutations directly impact immunotherapy efficacy. Therefore, we verified those highlighted key residues to see whether they can significantly distinguish immunotherapy patient groups. We have verified that the identified functional residues can successfully separate patient survival groups across breast, bladder, and pan-cancer datasets. Results demonstrate that GIHP improves the accuracy and interpretation capabilities of HLA-peptide prediction, and the findings of this study can be used to guide personalized cancer immunotherapy treatment. Codes and datasets are publicly accessible at: https://github.com/sdustSu/GIHP.

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.

PCDH11X mutation as a potential biomarker for immune checkpoint therapies in lung adenocarcinoma

Immune checkpoint inhibitors (ICIs) have achieved impressive success in lung adenocarcinoma (LUAD). However, the response to ICIs varies among patients, and predictive biomarkers are urgently needed. PCDH11X is frequently mutated in LUAD, while its role in ICI treatment is unclear. In this study, we curated genomic and clinical data of 151 LUAD patients receiving ICIs from three independent cohorts. Relations between PCDH11X and treatment outcomes of ICIs were examined. A melanoma cohort collected from five published studies, a pan-cancer cohort, and non-ICI-treated TCGA-LUAD cohort were also examined to investigate whether PCDH11X mutation is a specific predictive biomarker for LUAD ICI treatment. Among the three ICI-treated LUAD cohorts, PCDH11X mutation (PCDH11X-MUT) was associated with better clinical response compared to wild-type PCDH11X (PCDH11X-WT). While in ICI-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and the non-ICI-treated TCGA-LUAD cohort, no significant differences in overall survival (OS) were observed between the PCDH11X-MUT and PCDH11X-WT groups. PCDH11X mutation was associated with increased PD-L1 expression, tumor mutation burden (TMB), neoantigen load, DNA damage repair (DDR) mutations, and hot tumor microenvironment in TCGA-LUAD cohort. Our findings suggested that the PCDH11X mutation might serve as a specific biomarker to predict the efficacy of ICIs for LUAD patients. Considering the relatively small sample size of ICI-treated cohorts, future research with larger cohorts and prospective clinical trials will be essential for validating and further exploring the role of PCDH11X mutation in the context of immunotherapy outcomes in LUAD. KEY MESSAGES: PCDH11X mutation is associated with better clinical response compared to wild type PCDH11X in three ICIs-treated LUAD cohorts. In ICIs-treated melanoma cohort, the pan-cancer cohort excluding LUAD, and non-ICIs-treated TCGA-LUAD cohorts PCDH11X mutation is not associated with better clinical response, suggesting PCDH11X mutation might be a specific biomarker to predict the efficacy of ICIs treatment for LUAD patients. PCDH11X mutation is associated with increased PD-L1 expression, tumor mutation burden, and neoantigen load in TCGA-LUAD cohort. PCDH11X mutation is associated with hot tumor microenvironment in TCGA-LUAD cohort.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

CRISPR/Cas9-mediated knockout strategies for enhancing immunotherapy in breast cancer

Breast cancer, a prevalent disease with significant mortality rates, often presents treatment challenges due to its complex genetic makeup. This review explores the potential of combining Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) gene knockout strategies with immunotherapeutic approaches to enhance breast cancer treatment. The CRISPR/Cas9 system, renowned for its precision in inducing genetic alterations, can target and eliminate specific cancer cells, thereby minimizing off-target effects. Concurrently, immunotherapy, which leverages the immune system's power to combat cancer, has shown promise in treating breast cancer. By integrating these two strategies, we can potentially augment the effectiveness of immunotherapies by knocking out genes that enable cancer cells to evade the immune system. However, safety considerations, such as off-target effects and immune responses, necessitate careful evaluation. Current research endeavors aim to optimize these strategies and ascertain the most effective methods to stimulate the immune response. This review provides novel insights into the integration of CRISPR/Cas9-mediated knockout strategies and immunotherapy, a promising avenue that could revolutionize breast cancer treatment as our understanding of the immune system's interplay with cancer deepens.

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

INTRODUCTION

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

The Association between Mutational Signatures and Clinical Outcomes among Patients with Early-Onset Breast Cancer

Early-onset breast cancer (EoBC), defined by a diagnosis <40 years of age, is associated with poor prognosis. This study investigated the mutational landscape of non-metastatic EoBC and the prognostic relevance of mutational signatures using 100 tumour samples from Alberta, Canada. The MutationalPatterns package in R/Bioconductor was used to extract de novo single-base substitution (SBS) and insertion-deletion (indel) mutational signatures and to fit COSMIC SBS and indel signatures. We assessed associations between these signatures and clinical characteristics of disease, in addition to recurrence-free (RFS) and overall survival (OS). Five SBS and two indel signatures were extracted. The SBS13-like signature had higher relative contributions in the HER2-enriched subtype. Patients with higher than median contribution tended to have better RFS after adjustment for other prognostic factors (HR = 0.29; 95% CI: 0.08-1.06). An unsupervised clustering algorithm based on absolute contribution revealed three clusters of fitted COSMIC SBS signatures, but cluster membership was not associated with clinical variables or survival outcomes. The results of this exploratory study reveal various SBS and indel signatures may be associated with clinical features of disease and prognosis. Future studies with larger samples are required to better understand the mechanistic underpinnings of disease progression and treatment response in EoBC.

Biomarker discovery with quantum neural networks: a case-study in CTLA4-activation pathways

BACKGROUND

Biomarker discovery is a challenging task due to the massive search space. Quantum computing and quantum Artificial Intelligence (quantum AI) can be used to address the computational problem of biomarker discovery from genetic data.

METHOD

We propose a Quantum Neural Networks architecture to discover genetic biomarkers for input activation pathways. The Maximum Relevance-Minimum Redundancy criteria score biomarker candidate sets. Our proposed model is economical since the neural solution can be delivered on constrained hardware.

RESULTS

We demonstrate the proof of concept on four activation pathways associated with CTLA4, including (1) CTLA4-activation stand-alone, (2) CTLA4-CD8A-CD8B co-activation, (3) CTLA4-CD2 co-activation, and (4) CTLA4-CD2-CD48-CD53-CD58-CD84 co-activation.

CONCLUSION

The model indicates new genetic biomarkers associated with the mutational activation of CLTA4-associated pathways, including 20 genes: CLIC4, CPE, ETS2, FAM107A, GPR116, HYOU1, LCN2, MACF1, MT1G, NAPA, NDUFS5, PAK1, PFN1, PGAP3, PPM1G, PSMD8, RNF213, SLC25A3, UBA1, and WLS. We open source the implementation at: https://github.com/namnguyen0510/Biomarker-Discovery-with-Quantum-Neural-Networks .

Adjuvant PD-1 Checkpoint Inhibition in Early Cutaneous Melanoma: Immunological Mode of Action and the Role of Ultraviolet Radiation

Melanoma ranks as the fifth most common solid cancer in adults worldwide and is responsible for a significant proportion of skin-tumor-related deaths. The advent of immune checkpoint inhibition with anti-programmed death protein-1 (PD-1) antibodies has revolutionized the adjuvant treatment of high-risk, completely resected stage III/IV melanoma. However, not all patients benefit equally. Current strategies for improving outcomes involve adjuvant treatment in earlier disease stages (IIB/C) as well as perioperative treatment approaches. Interfering with T-cell exhaustion to counteract cancer immune evasion and the immunogenic nature of melanoma is key for anti-PD-1 effectiveness. Yet, the biological rationale for the efficacy of adjuvant treatment in clinically tumor-free patients remains to be fully elucidated. High-dose intermittent sun exposure (sunburn) is a well-known primary risk factor for melanomagenesis. Also, ultraviolet radiation (UVR)-induced immunosuppression may impair anti-cancer immune surveillance. In this review, we summarize the current knowledge about adjuvant anti-PD-1 blockade, including a characterization of the main cell types most likely responsible for its efficacy. In conclusion, we propose that local and systemic immunosuppression, to some extent UVR-mediated, can be restored by adjuvant anti-PD-1 therapy, consequently boosting anti-melanoma immune surveillance and the elimination of residual melanoma cell clones.

Molecular patterns of resistance to immune checkpoint blockade in melanoma

Immune checkpoint blockade (ICB) has improved outcome for patients with metastatic melanoma but not all benefit from treatment. Several immune- and tumor intrinsic features are associated with clinical response at baseline. However, we need to further understand the molecular changes occurring during development of ICB resistance. Here, we collect biopsies from a cohort of 44 patients with melanoma after progression on anti-CTLA4 or anti-PD1 monotherapy. Genetic alterations of antigen presentation and interferon gamma signaling pathways are observed in approximately 25% of ICB resistant cases. Anti-CTLA4 resistant lesions have a sustained immune response, including immune-regulatory features, as suggested by multiplex spatial and T cell receptor (TCR) clonality analyses. One anti-PD1 resistant lesion harbors a distinct immune cell niche, however, anti-PD1 resistant tumors are generally immune poor with non-expanded TCR clones. Such immune poor microenvironments are associated with melanoma cells having a de-differentiated phenotype lacking expression of MHC-I molecules. In addition, anti-PD1 resistant tumors have reduced fractions of PD1+ CD8+ T cells as compared to ICB naïve metastases. Collectively, these data show the complexity of ICB resistance and highlight differences between anti-CTLA4 and anti-PD1 resistance that may underlie differential clinical outcomes of therapy sequence and combination.

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

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

Cancer-associated polybromo-1 bromodomain 4 missense variants variably impact bromodomain ligand binding and cell growth suppression

The polybromo, brahma-related gene 1-associated factors (PBAF) chromatin remodeling complex subunit polybromo-1 (PBRM1) contains six bromodomains that recognize and bind acetylated lysine residues on histone tails and other nuclear proteins. PBRM1 bromodomains thus provide a link between epigenetic posttranslational modifications and PBAF modulation of chromatin accessibility and transcription. As a putative tumor suppressor in several cancers, PBRM1 protein expression is often abrogated by truncations and deletions. However, ∼33% of PBRM1 mutations in cancer are missense and cluster within its bromodomains. Such mutations may generate full-length PBRM1 variant proteins with undetermined structural and functional characteristics. Here, we employed computational, biophysical, and cellular assays to interrogate the effects of PBRM1 bromodomain missense variants on bromodomain stability and function. Since mutations in the fourth bromodomain of PBRM1 (PBRM1-BD4) comprise nearly 20% of all cancer-associated PBRM1 missense mutations, we focused our analysis on PBRM1-BD4 missense protein variants. Selecting 16 potentially deleterious PBRM1-BD4 missense protein variants for further study based on high residue mutational frequency and/or conservation, we show that cancer-associated PBRM1-BD4 missense variants exhibit varied bromodomain stability and ability to bind acetylated histones. Our results demonstrate the effectiveness of identifying the unique impacts of individual PBRM1-BD4 missense variants on protein structure and function, based on affected residue location within the bromodomain. This knowledge provides a foundation for drawing correlations between specific cancer-associated PBRM1 missense variants and distinct alterations in PBRM1 function, informing future cancer personalized medicine approaches.

Modulator of TMB-associated immune infiltration (MOTIF) predicts immunotherapy response and guides combination therapy

Patients with high tumor mutational burden (TMB) levels do not consistently respond to immune checkpoint inhibitors (ICIs), possibly because a high TMB level does not necessarily result in adequate infiltration of CD8+ T cells. Using bulk ribonucleic acid sequencing (RNA-seq) data from 9311 tumor samples across 30 cancer types, we developed a novel tool called the modulator of TMB-associated immune infiltration (MOTIF), which comprises genes that can determine the extent of CD8+ T cell infiltration prompted by a certain TMB level. We confirmed that MOTIF can accurately reflect the integrity and defects of the cancer-immunity cycle. By analyzing 84 human single-cell RNA-seq datasets from 32 types of solid tumors, we revealed that MOTIF can provide insights into the diverse roles of various cell types in the modulation of CD8+ T cell infiltration. Using pretreatment RNA-seq data from 13 ICI-treated cohorts, we validated the use of MOTIF in predicting CD8+ T cell infiltration and ICI efficacy. Among the components of MOTIF, we identified EMC3 as a negative regulator of CD8+ T cell infiltration, which was validated via in vivo studies. Additionally, MOTIF provided guidance for the potential combinations of programmed death 1 blockade with certain immunostimulatory drugs to facilitate CD8+ T cell infiltration and improve ICI efficacy.

Comprehensive pan-cancer analysis of 33 human cancers reveals immunotherapeutic value of focal adhesion tyrosine kinase

The immune environment in tumors is the key factor affecting the survival and immunotherapeutic response of patients. This research aimed to explore the underlying association between focal adhesion tyrosine kinase (FAK/PTK2) and cancer immunotherapy in 33 human cancers. Gene expression data and clinical features of 33 cancers were retrieved from the Cancer Genome Atlas Database. The immunotherapy cohorts included GSE67501, GSE78220, and IMVIGOR210, which were derived from the comprehensive gene expression database or from previous studies. Clinical parameters including patient age, gender, survival rate, and tumor stage were analyzed to evaluate the prognostic value of FAK/PTK2. FAK/PTK2 activity was detected by single-sample gene set enrichment analysis and used to compare the difference between FAK/PTK2 transcriptome and protein expression levels. To better understand the role of FAK/PTK2 in cancer immunotherapy, we analyzed its correlations with tumor microenvironment and with immune processes/elements (e.g., immune cell infiltration, immunosuppressants, and stimulants) and major histocompatible complexes. Potential pathways associated with FAK/PTK2 signaling in cancers were also explored. Correlations between FAK/PTK2 and 2 immunotherapeutic biomarkers (tumor mutation load and microsatellite instability) were studied. Finally, the 3 independent immunotherapy cohorts were used to study the relationship between FAK/PTK2 and immunotherapeutic response. Although FAK/PTK2 is not closely associated with age (13/33), gender (5/33), or tumor stage (5/33) in any of the studied human cancers, it has potential prognostic value for predicting patient survival. Consistency between FAK/PTK2 activity and expression exists in some cancers (3/33). Generally, FAK/PTK2 is robustly correlated with immune cell infiltration, immune modulators, and immunotherapeutic markers. Moreover, high FAK/PTK2 expression is significantly related to immune-relevant pathways. However, FAK/PTK2 is not significantly correlated with the immunotherapeutic response. Research on the immunotherapeutic value of FAK/PTK2 in 33 human cancers provides evidence regarding the function of FAK/PTK2 and its role in clinical treatment. However, given the use of a bioinformatics approach, our results are preliminary and require further validation.

Banxia-Shengjiang drug pair inhibits gastric cancer development and progression by improving body immunity

To investigate the mechanism of action of Banxia-Shengjiang drug pair on the inhibition of gastric cancer (GC) using network pharmacology and bioinformatics techniques. The action targets of the Banxia (Pinellia ternata (Thunb.) Makino) -Shengjiang (Zingiber officinale Roscoe) drug pair obtained from the TCMSP database were intersected with differentially expressed genes (DEGs) and GC-related genes, and the intersected genes were analyzed for pathway enrichment to identify the signaling pathways and core target genes. Subsequently, the core target genes were analyzed for clinical relevance gene mutation analysis, methylation analysis, immune infiltration analysis and immune cell analysis. Finally, by constructing the PPI network of hub genes and corresponding active ingredients, the key active ingredients of the Banxia-Shengjiang drug pair were screened for molecular docking with the hub genes. In this study, a total of 557 target genes of Banxia-Shengjiang pairs, 7754 GC-related genes and 1799 DEGs in GC were screened. Five hub genes were screened, which were PTGS2, MMP9, PPARG, MMP2, and CXCR4. The pathway enrichment analyses showed that the intersecting genes were associated with RAS/MAPK signaling pathway. In addition, the clinical correlation analysis showed that hub genes were differentially expressed in GC and was closely associated with immune infiltration and immunotherapy. The results of single nucleotide variation (SNV) and copy number variation (CNV) indicated that mutations in the hub genes were associated with the survival of gastric cancer patients. Finally, the PPI network and molecular docking results showed that PTGS2 and MMP9 were potentially important targets for the inhibition of GC by Banxia-Shengjiang drug pair, while cavidine was an important active ingredient for the inhibition of GC by Banxia-Shengjiang drug pair. Banxia-Shengjiang drug pair may regulate the immune function and inhibit GC by modulating the expression of core target genes such as RAS/MAPK signaling pathway, PTGS2 and MMP9.

Cathepsin V is correlated with the prognosis and tumor microenvironment in liver cancer

Recent studies have shown that high cell cycle activity negatively correlates with antitumor immunity in certain cancer types. However, a similar correlation has not been proven in liver cancer. We downloaded transcriptomic profiles of the cancer genome atlas-liver hepatocellular carcinoma (TCGA-LIHC) and assessed the cell cycle distribution of samples using single sample gene set enrichment analysis (ssGSEA), termed the cell cycle score (CCS). We obtained cell cycle-related differentially expressed prognostic genes and identified CENPA, CDC20, and CTSV using LASSO regression. We studied the effect of CTSV on clinical features and immune alterations in liver cancer based on TCGA-LIHC data. In vitro and in vivo experiments were performed to validate the role of CTSV in liver cancer using liver cancer cell lines and tissues. We found that the CCS closely correlated with the clinical features and prognosis of patients in TCGA-LIHC. Analysis of differentially expressed genes (DEGs), univariate Cox regression, and least absolute shrinkage and selection operator (LASSO) regression identified cathepsin V (CTSV) with prognostic significance in LIHC. Importantly, single-gene survival analysis of CTSV using microarray and sequencing data indicated that high levels of CTSV expression correlated with an unfavorable prognosis in various cancers. Gene set enrichment analysis revealed that high CTSV expression closely correlated with decreased expression of metabolic genes and increased expression of cell cycle genes. Furthermore, difference and correlation analyses of the relationship between CTSV expression and immune infiltrates, determined using CIBERSORT and TIMER algorithms, revealed that CTSV expression correlated with macrophages and CD4+ T cells. In vitro and in vivo experiments revealed that knockdown of CTSV inhibited liver cancer cells proliferation. Immunohistochemical staining showed that high CTSV expression correlated with macrophage infiltration in liver cancer tissues, predicted a poor prognosis, and is associated with the effectiveness of hepatocellular carcinoma treatment. In couclusion, CTSV is a novel cell cycle-associated gene with clinical significance in HCC.

SOX17 enables immune evasion of early colorectal adenomas and cancers

A hallmark of cancer is the avoidance of immune destruction. This process has been primarily investigated in locally advanced or metastatic cancer1-3; however, much less is known about how pre-malignant or early invasive tumours evade immune detection. Here, to understand this process in early colorectal cancers (CRCs), we investigated how naive colon cancer organoids that were engineered in vitro to harbour Apc-null, KrasG12D and Trp53-null (AKP) mutations adapted to the in vivo native colonic environment. Comprehensive transcriptomic and chromatin analyses revealed that the endoderm-specifying transcription factor SOX17 became strongly upregulated in vivo. Notably, whereas SOX17 loss did not affect AKP organoid propagation in vitro, its loss markedly reduced the ability of AKP tumours to persist in vivo. The small fraction of SOX17-null tumours that grew displayed notable interferon-γ (IFNγ)-producing effector-like CD8+ T cell infiltrates in contrast to the immune-suppressive microenvironment in wild-type counterparts. Mechanistically, in both endogenous Apc-null pre-malignant adenomas and transplanted organoid-derived AKP CRCs, SOX17 suppresses the ability of tumour cells to sense and respond to IFNγ, preventing anti-tumour T cell responses. Finally, SOX17 engages a fetal intestinal programme that drives differentiation away from LGR5+ tumour cells to produce immune-evasive LGR5- tumour cells with lower expression of major histocompatibility complex class I (MHC-I). We propose that SOX17 is a transcription factor that is engaged during the early steps of colon cancer to orchestrate an immune-evasive programme that permits CRC initiation and progression.

Prognostic and predictive biomarkers in melanoma

Biomarkers help to inform the clinical management of patients with melanoma. For patients with clinically localised primary melanoma, biomarkers can help to predict post-surgical outcome (including via the use of risk prediction tools), better select patients for sentinel lymph node biopsy, and tailor catch-all follow-up protocols to the individual. Systemic drug treatments, including immune checkpoint inhibitor (ICI) therapies and BRAF-targeted therapies, have radically improved the prognosis of metastatic (stage III and IV) cutaneous melanoma patients, and also shown benefit in the earlier setting of stage IIB/C primary melanoma. Unfortunately, a response is far from guaranteed. Here, we review clinically relevant, established, and emerging, prognostic, and predictive pathological biomarkers that refine clinical decision-making in primary and metastatic melanoma patients. Gene expression profile assays and nomograms are emerging tools for prognostication and sentinel lymph node risk prediction in primary melanoma patients. Biomarkers incorporated into clinical practice guidelines include BRAF V600 mutations for the use of targeted therapies in metastatic cutaneous melanoma, and the HLA-A∗02:01 allele for the use of a bispecific fusion protein in metastatic uveal melanoma. Several predictive biomarkers have been proposed for ICI therapies but have not been incorporated into Australian clinical practice guidelines. Further research, validation, and assessment of clinical utility is required before more prognostic and predictive biomarkers are fluidly integrated into routine care.

Assessment of human leukocyte antigen-based neoantigen presentation to determine pan-cancer response to immunotherapy

Despite the central role of human leukocyte antigen class I (HLA-I) in tumor neoantigen presentation, quantitative determination of presentation capacity remains elusive. Based on a pooled pan-cancer genomic dataset of 885 patients treated with immune checkpoint inhibitors (ICIs), we developed a score integrating the binding affinity of neoantigens to HLA-I, as well as HLA-I allele divergence, termed the HLA tumor-Antigen Presentation Score (HAPS). Patients with a high HAPS were more likely to experience survival benefit following ICI treatment. Analysis of the tumor microenvironment indicated that the antigen presentation pathway was enriched in patients with a high HAPS. Finally, we built a neural network incorporating factors associated with neoantigen production, presentation, and recognition, which exhibited potential for differentiating cancer patients likely to benefit from ICIs. Our findings highlight the clinical utility of evaluating HLA-I tumor antigen presentation capacity and describe how ICI response may depend on HLA-mediated immunity.

STING-targeted PET tracer for early assessment of tumor immunogenicity in colorectal cancer after chemotherapy

PURPOSE

To optimize chemotherapy regimens and improve the effectiveness of chemotherapy combined with immunotherapy, a PET tracer specifically targeting the stimulator of interferon genes (STING), denoted as [18F]FBTA was used to monitor the early changes in tumor immunogenicity after chemotherapy in colorectal cancer (CRC) mice.

METHODS

The toluene sulfonate precursor was labeled with 18F to produce the STING targeted probe-[18F]FBTA. [18F]FBTA-PET imaging and biodistribution were performed using CRC mice treated with oxaliplatin (OXA) or cisplatin (CDDP). CRC mice were also treated with low (CDDP-LD: 1 mg/kg) or medium (CDDP-MD: 2.5 mg/kg) doses of CDDP, and subjected to PET imaging and biodistribution. The effects of different chemotherapeutic agents and different doses of CDDP on tumor innate immunity were verified by flow cytometry and immunohistochemistry.

RESULTS

PET imaging of CRC mice exhibited notably enhanced tumor uptake in the early phase of chemotherapy with treatment with OXA (3.09 ± 0.25%ID/g) and CDDP (4.01 ± 0.18%ID/g), especially in the CDDP group. The PET-derived tumor uptake values have strong correlations with STING immunohistochemical score. Flow cytometry showed both agents led to DCs and macrophages infiltration in tumors. Compared with OXA, CDDP treatment recruits more DCs and macrophages in CRC tumors. Both CDDP-LD and CDDP-MD treatment elevated uptake in CRC tumors, especially in CDDP-MD group. Immunohistochemistry and flow cytometry confirmed CDDP-MD treatment recruits more DCs and macrophages than CDDP-LD treatment.

CONCLUSION

Overall, the STING-targeted tracer-[18F]FBTA was demonstrated to monitor early changes in tumor immunogenicity in CRC mice after chemotherapy. Besides, the STING-targeted strategy may help to select the appropriate chemotherapy regimen, including chemotherapeutic agents and doses, which further improve clinical decision making for combination immunotherapy after chemotherapy for CRC.

Identification and validation of the association of Janus kinase 2 mutations with the response to immune checkpoint inhibitor therapy

BACKGROUND

Janus kinase 2 (JAK2) mutation plays an important role in T cell immunity. However, the effect of JAK2 mutation on immunotherapy is largely uncharacterized.

METHODS

In this study, we analyzed the effect of JAK2 mutation on the efficacy and outcomes of immune checkpoint inhibitor (ICI) therapy in the discovery cohort (n = 662) and the verification cohort (n = 1423). Furthermore, we explored the association of JAK2 mutation with the tumor immune microenvironment in a multiomics cohort.

RESULTS

In the discovery cohort (n = 662), JAK2 mutant-type patients had a better objective response rate (58.8% vs. 26.7%, P = 0.010), durable clinical benefit (64.7% vs. 38.9%, P = 0.043), progression-free survival (hazard ratio [HR] = 0.431, P = 0.015), and overall survival (HR = 0.378, P = 0.025), relative to JAK2 wild-type patients. Moreover, we further verified the prognostic significance of JAK2 mutation in an independent ICI treatment cohort with a larger sample size (n = 1423). In addition, we discovered that the JAK2 mutation was remarkably related to increased immunogenicity, such as a higher TMB, higher expression of costimulatory molecules and stimulation of antigen processing mechanisms. In addition, JAK2 mutation was positively correlated with activated anticancer immunity, such as infiltration of various immune cells and higher expression of chemokines.

CONCLUSION

Our study demonstrates that JAK2 mutation is a novel marker that can be used to effectively predict prognosis and response to ICI therapy.

A Comparative Transcriptomic Study and Key Gene Targeting of Lamprey Gonadal Immune Response

The mammalian testis and ovary possess special immunocompetence, which is central to provide protection against pathogens. However, the innate immune responses to immune challenges in lamprey gonads are poorly understood. In this study, we extracted RNA from testis and ovary tissues of lampreys at 0 hour, 8 hours and 17 days after lipopolysaccharides (LPS) stimulation and performed transcriptome sequencing. While the transcriptome profiles of the two tissues were different for the most part, genes LIP, LECT2, LAL2, GRN, ITLN, and C1q were found to be the most significantly up-regulated genes in both. Quantitative Real-time PCR (qRT-PCR) analysis confirmed that these genes were upregulated after stimulation. Furthermore, immunohistochemical staining showed that these genes in lamprey gonads are expressed in high quantities and have a specific distribution. Taken together, our results suggest that these genes could play an essential role in response of the gonads to LPS induction. This research establishes a basis for investigating the immune mechanism of vertebrate gonads and presents a fresh concept for gaining insight into the evolutionary development of jawless vertebrates.

MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma

BACKGROUND

The tumor immune microenvironment can influence the prognosis and treatment response to immunotherapy. We aimed to develop a non-invasive radiomic signature in high-grade glioma (HGG) to predict the absolute density of tumor-associated macrophages (TAMs), the preponderant immune cells in the microenvironment of HGG. We also aimed to evaluate the association between the signature, and tumor immune phenotype as well as response to immunotherapy.

METHODS

In this retrospective setting, total of 379 patients with HGG from three independent cohorts were included to construct a radiomic model named Radiomics Immunological Biomarker (RIB) for predicting the absolute density of M2-like TAM using the mRMR feature ranking method and LASSO classifier. Among them, 145 patients from the TCGA microarray cohort were randomly allocated into a training set (N=101) and an internal validation set (N=44), while the immune-phenotype cohort (N=203) and the immunotherapy-treated cohort (N=31, patients from a prospective clinical trial treated with DC vaccine) recruited from Huashan Hospital were used as two external validation sets. The immunotherapy-treated cohort was also used to evaluate the relationship between RIB and immunotherapy response. Radiogenomic analysis was performed to find functional annotations using RNA sequencing data from TAM cells.

RESULTS

An 11-feature radiomic model for M2-like TAM was developed and validated in four datasets of HGG patients (area under the curve = 0.849, 0.719, 0.674, and 0.671) using MRI images of post contrast enhanced T1-weighted (T1CE). Patients with high RIB scores had a strong inflammatory response. Four hub-genes (SLC7A7, RNASE6, HLA-DRB1 and CD300A) expressed by TAM were identified to be closely related to the RIB, providing important evidence for biological interpretation. Only individuals with a high RIB score were shown to have survival benefits from DC vaccine [DC vaccine vs. Placebo: median progression-free survival (mPFS), 10.0 mos vs. 4.5 mos, HR=0.17, P=0.0056, 95%CI=0.041-0.68; median overall survival (mOS), 15.0 mos vs. 7.0 mos, HR=0.17, P =0.0076, 95%CI=0.04-0.68]. Multivariate analyses also confirmed that treatment by DC vaccine was an independent factor for improved survival in the high RIB score group. However, in the low RIB score group, DC vaccine was not associated with improved survival. Furthermore, a radiomic nomogram based on the RIB score and clinical factors could efficiently predict the 1-, 2-, and 3-year survival rates, as confirmed by ROC curve analysis (AUC for 1-, 2- and 3-year survival: 0.705, 0.729 and 0.684, respectively).

CONCLUSIONS

The radiomic model could allow for non-invasive assessment of the absolute density of TAM from MRI images in HGG patients. Of note, our RIB model is the first immunological radiomic model confirmed to have the ability to predict survival benefits from DC vaccine in gliomas, thereby providing a novel tool to inform treatment decisions and monitor patient treatment course by radiomics.

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

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

Mutation status of the KMT2 family associated with immune checkpoint inhibitors (ICIs) therapy and implicating diverse tumor microenvironments

Mounting evidence suggests a strong association between tumor immunity and epigenetic regulation. The histone-lysine N-methyltransferase 2 (KMT2) family plays a crucial role in the methylation of histone H3 at lysine 4. By influencing chromatin structure and DNA accessibility, this modification serves as a key regulator of tumor progression and immune tolerance across various tumors. These findings highlight the potential significance of the KMT2 family in determining response to immune checkpoint inhibitor (ICI) therapy, which warrants further exploration. In this study, we integrated four ICI-treated cohorts (n = 2069) across 10 cancer types and The Cancer Genome Atlas pan-cancer cohort and conducted a comprehensive clinical and bioinformatic analysis. Our study indicated that patients with KMT2 family gene mutations benefited more from ICI therapy in terms of overall survival (P < 0.001, hazard ratio [HR] = 0.733 [95% confidence interval (CI): 0.632-0.850]), progression-free survival (P = 0.002, HR = 0.669 [95% CI: 0.518-0.864]), durable clinical benefit (P < 0.001, 54.1% vs. 32.6%), and objective response rate (P < 0.001, 40.6% vs. 22.0%). Through a comprehensive analysis of the tumor microenvironment across different KMT2 mutation statuses, we observed that tumors harboring the KMT2 mutation exhibited enhanced immunogenicity, increased infiltration of immune cells, and higher levels of immune cell cytotoxicity, suggesting a propensity towards a "hot tumor" phenotype. Therefore, our study indicates a potential association between KMT2 mutations and a more favorable response to ICI therapy and implicates different tumor microenvironments associated with ICI therapy response.

Conformational diversity and protein-protein interfaces in drug repurposing in Ras signaling pathway

We focus on drug repurposing in the Ras signaling pathway, considering structural similarities of protein-protein interfaces. The interfaces formed by physically interacting proteins are found from PDB if available and via PRISM (PRotein Interaction by Structural Matching) otherwise. The structural coverage of these interactions has been increased from 21 to 92% using PRISM. Multiple conformations of each protein are used to include protein dynamics and diversity. Next, we find FDA-approved drugs bound to structurally similar protein-protein interfaces. The results suggest that HIV protease inhibitors tipranavir, indinavir, and saquinavir may bind to EGFR and ERBB3/HER3 interface. Tipranavir and indinavir may also bind to EGFR and ERBB2/HER2 interface. Additionally, a drug used in Alzheimer's disease can bind to RAF1 and BRAF interface. Hence, we propose a methodology to find drugs to be potentially used for cancer using a dataset of structurally similar protein-protein interface clusters rather than pockets in a systematic way.

Comprehensive molecular analysis identifies RET alterations association with response of ICIs in multi-immunotherapy cohorts

BACKGROUND

The RET gene, which is frequently mutated across many types of cancer, has been proven to be critically involved in tumorigenesis and tumour development; however, its prediction of the therapeutic efficacy of immune checkpoint inhibitor (ICI) therapy remains to be elucidated. The present research aims to investigate the association between RET mutations and the efficiency of ICI therapy.

METHOD

We analysed the role of RET mutations in predicting the prognosis of patients receiving ICIs therapy in the discovery cohort and validated it in the validation cohort. Then, multi-omics data from TCGA pan-cancer cohort was employed to propose the association between RET mutations and tumour inflamed anti-tumour immune response and tumour antigenicity.

RESULTS

Our study revealed that among 606 cases and across five types of cancer, RET mutation was associated with better clinical outcomes for ICIs therapy, including elevated response rate, longer progression-free survival PFS, and longer overall survival OS. Multivariate analysis showed that RET mutation could independently predict the prognosis of patients treated with ICIs, after adjusting cancer types. The predictive value of RET status for the OS of patients treated with ICIs immunotherapy was further validated in the validation cohort (n = 1,409). Subgroup analysis suggested that only the monotherapy group showed significant differences in OS(P < 0.05) and PFS(P < 0.05) between RET-wildtype tumours and RET-mutant tumours. Multi-omics data analysis revealed potential anti-tumour immunity mechanisms of RET mutations, suggesting that RET-mutant tumours have enhanced immunogenicity, higher expression of immune checkpoints and chemokines, and higher immune cell infiltration than those observed in RET-wildtype tumours; thus, potentially indicating a more favourable response to immunotherapy.

CONCLUSIONS

RET mutation may be a predictive biomarker of enhanced response to ICIs therapy. Extensive investigation of the underlying molecular mechanisms and prospective studies are needed in the future.

Identification of ATM Mutation as a Potential Prognostic Biomarker for Immune Checkpoint Inhibitors Therapy

BACKGROUND

Ataxia telangiectasia mutated (ATM), an apical DNA damage response gene, is a commonly mutated gene in tumors, and its mutation could strengthen tumor immunogenicity and alter the expression of PD-L1, which potentially contributes to immune checkpoint inhibitors (ICIs) therapy.

METHODS

The characteristics of ATM mutation and its relationship with the ICIs-treated clinical prognosis have been analyzed comprehensively in this paper. The overall frequency of ATM mutations has been found to be 4% (554/10953) in the cancer genome atlas (TCGA) cohort.

RESULTS

Both the TMB and MSI levels in patients with ATM mutations were significantly higher than those in patients without mutations (P < 0.0001). The median TMB was positively correlated with the frequency of ATM mutations (r = 0.54, P = 0.003). In the TCGA cohort, patients with ATM mutations had better clinical benefits in terms of overall survival (OS, hazard ratio (HR) = 0.736, 95% CI = 0.623 - 0.869), progression-free survival (PFS, HR = 0.761, 95% CI = 0.652 - 0.889), and disease-free survival (DFS, HR = 0.686, 95% CI = 0.512 - 0.919)] than patients without ATM mutations. Subsequently, the verification results showed ATM mutations to be significantly correlated with longer OS in ICIs-treated patients (HR = 0.710, 95% CI = 0.544 - 0.928). Further exploration indicated ATM mutation to be significantly associated with regulated anti-tumor immunity (P < 0.05).

CONCLUSION

Our findings highlight the value of ATM mutation as a promising biomarker to predict ICIs therapy in multiple tumors.

BLM mutation is associated with increased tumor mutation burden and improved survival after immunotherapy across multiple cancers

BACKGROUND

BLM encodes a RecQ DNA helicase that regulates genomic stability, and its mutations are associated with increased cancer susceptibility. Here, we show a multifaceted role of BLM mutations in tumorigenesis and immunotherapy.

METHODS AND RESULTS

A total of 10,967 cancer samples from the cancer genome atlas database were analyzed, 1.6% of which harbored BLM somatic mutations. BLM mutation was found to be associated with increased tumor mutation burden and more immune-active tumor microenvironment in these patients. Moreover, clinical data of 2785 patients from nine immunotherapy studies were analyzed to study BLM mutations' impact on immunotherapy. Among them, 69 patients harbored BLM mutations, and interestingly, they had significantly higher survival probability than patients without BLM mutations. Cancer patients with BLM mutations had higher complete response and partial response rates, but lower progressive disease rate than BLM nonmutant patients.

CONCLUSION

Our study shows that BLM mutation is related to improved survival after immunotherapy across multiple cancers.

Recent advances in personalized cancer immunotherapy with immune checkpoint inhibitors, T cells and vaccines

The results of genomic and molecular profiling of cancer patients can be effectively applied to immunotherapy agents, including immune checkpoint inhibitors, to select the most appropriate treatment. In addition, accurate prediction of neoantigens facilitates the development of individualized cancer vaccines and T-cell therapy. This review summarizes the biomarker(s) predicting responses to immune checkpoint inhibitors and focuses on current strategies to identify and isolate neoantigen-reactive T cells as well as the clinical development of neoantigen-based therapeutics. The results suggest that maximal T-cell stimulation and expansion can be achieved with combination therapies that enhance antigen-presenting cells' function and optimal T-cell priming in lymph nodes.

Identifying survival of pan-cancer patients under immunotherapy using genomic mutation signature with large sample cohorts

Although immune checkpoint inhibitors have led to durable clinical response in multiple cancers, only a small proportion of patients respond to this treatment. Therefore, we aim to develop a predictive model that utilizes gene mutation profiles to accurately identify the survival of pan-cancer patients with immunotherapy. Here, we develop and evaluate three different nomograms using two cohorts containing 1,594 cancer patients whose mutation profiles are obtained by MSK-IMPACT sequencing and 230 cancer patients receiving whole-exome sequencing, respectively. Using eighteen genes (SETD2, BRAF, NCOA3, LATS1, IL7R, CREBBP, TET1, EPHA7, KDM5C, MET, KMT2D, RET, PAK7, CSF1R, JAK2, FAT1, ASXL1 and SPEN), the first nomogram stratifies patients from both cohorts into High-Risk and Low-Risk groups. Pan-cancer patients in the High-Risk group exhibit significantly shorter overall survival and progression-free survival than patients in the Low-Risk group in both cohorts. Meanwhile, the first nomogram also accurately identifies the survival of patients with melanoma or lung cancer undergoing immunotherapy, or pan-cancer patients treated with anti-PD-1/PD-L1 inhibitor or anti-CTLA-4 inhibitor. The model proposed is not a prognostic model for the survival of pan-cancer patients without immunotherapy, but a simple, effective and robust predictive model for pan-cancer patients' survival under immunotherapy, and could provide valuable assistance for clinical practice.

Development of Tumor Markers for Breast Cancer Immunotherapy

Although breast cancer treatment has been developed remarkably in recent years, it remains the primary cause of death among women. Immune checkpoint blockade therapy has significantly altered the way breast cancer is treated, although not all patients benefit from the changes. At present, the most effective mechanism of immune checkpoint blockade application in malignant tumors is not clear and efficacy may be influenced by many factors, including host, tumor, and tumor microenvironment dynamics. Therefore, there is a pressing need for tumor immunomarkers that can be used to screen patients and help determine which of them would benefit from breast cancer immunotherapy. At present, no single tumor marker can predict treatment efficacy with sufficient accuracy. Multiple markers may be combined to more accurately pinpoint patients who will respond favorably to immune checkpoint blockade medication. In this review, we have examined the breast cancer treatments, developments in research on the role of tumor markers in maximizing the clinical efficacy of immune checkpoint inhibitors, prospects for the identification of novel therapeutic targets, and the creation of individualized treatment plans. We also discuss how tumor markers can provide guidance for clinical practice.

The next bastion to be conquered in immunotherapy: microsatellite stable colorectal cancer

Colorectal cancer (CRC) is the second leading cause of cancer-related deaths worldwide, and its incidence continues to rise, particularly in developing countries. The advent of immune checkpoint inhibitors (ICIs) has represented a significant advancement in CRC treatment. Deficient mismatch repair (dMMR) or high microsatellite instability (MSI-H) serves as a biomarker for immunotherapy, with dMMR/MSI-H CRC exhibiting significantly better response rates to immunotherapy compared to proficient mismatch repair (pMMR)or microsatellite stable (MSS) CRC. While some progress has been made in the treatment of pMMR/MSS CRC in recent years, it remains a challenging issue in clinical practice. The tumor microenvironment (TME) plays a crucial role not only in the development and progression of CRC but also in determining the response to immunotherapy. Understanding the characteristics of the TME in pMMR/MSS CRC could offer new insights to enhance the efficacy of immunotherapy. In this review, we provide an overview of the current research progress on the TME characteristics and advancements in immunotherapy for pMMR/MSS CRC.

PathwayTMB: A pathway-based tumor mutational burden analysis method for predicting the clinical outcome of cancer immunotherapy

Immunotherapy has become one of the most promising therapy methods for cancer, but only a small number of patients are responsive to it, indicating that more effective biomarkers are urgently needed. This study developed a pathway analysis method, named PathwayTMB, to identify genomic mutation pathways that serve as potential biomarkers for predicting the clinical outcome of immunotherapy. PathwayTMB first calculates the patient-specific pathway-based tumor mutational burden (PTMB) to reflect the cumulative extent of mutations for each pathway. It then screens mutated survival benefit-related pathways to construct an immune-related prognostic signature based on PTMB (IPSP). In a melanoma training set, IPSP-high patients presented a longer overall survival and a higher response rate than IPSP-low patients. Moreover, the IPSP showed a superior predictive effect compared with TMB. In addition, the prognostic and predictive value of the IPSP was consistently validated in two independent validation sets. Finally, in a multi-cancer dataset, PathwayTMB also exhibited good performance. Our results indicate that PathwayTMB could identify the mutation pathways for predicting immunotherapeutic survival, and their combination may serve as a potential predictive biomarker for immune checkpoint inhibitor therapy.

Identification and targeting of cancer-associated fibroblast signature genes for prognosis and therapy in Cutaneous melanoma

BACKGROUND

Cancer-associated fibroblasts (CAFs) play pivotal roles in tumor invasion and metastasis. However, studies on CAF biomarkers in Cutaneous Melanoma (CM) are still scarce. This study aimed to explore the potential CAF biomarkers in CM, propose the potential therapeutic targets, and provide new insights for targeted therapy of CAFs in CM.

METHODS

We utilized weighted gene co-expression network analysis to identify CAF signature genes in CM, and conducted comprehensive bioinformatics analysis on the CAF risk score established by these genes. Moreover, single-cell sequencing analysis, spatial transcriptome analysis, and cell experiments were utilized for verifying the expression and distribution pattern of signature genes. Furthermore, molecular docking was employed to screen potential target drugs.

RESULTS

FBLN1 and COL5A1, two crucial CAF signature genes, were screened to establish the CAF risk score. Subsequently, a comprehensive bioinformatic analysis of the CAF risk score revealed that high-risk score group was significantly enriched in pathways associated with tumor progression. Besides, CAF risk score was significantly negatively correlated with clinical prognosis, immunotherapy response, and tumor mutational burden in CM patients. In addition, FBLN1 and COL5A1 were further identified as CAF-specific biomarkers in CM by multi-omics analysis and experimental validation. Eventually, based on these two targets, Mifepristone and Dexamethasone were screened as potential anti-CAFs drugs.

CONCLUSION

The findings indicated that FBLN1 and COL5A1 were the CAF signature genes in CM, which were associated with the progression, treatment, and prognosis of CM. The comprehensive exploration of CAF signature genes is expected to provide new insight for clinical CM therapy.

Incidental detection of FGFR3 fusion via liquid biopsy leading to earlier diagnosis of urothelial carcinoma

The rising utilization of circulating tumor DNA (ctDNA) assays in Precision Oncology may incidentally detect genetic material from secondary sources. It is important that such findings are recognized and properly leveraged for both diagnosis and monitoring of response to treatment. Here, we report a patient in whom serial cell-free DNA (cfDNA) monitoring for his known prostate adenocarcinoma uncovered the emergence of an unexpected FGFR3-TACC3 gene fusion, a BRCA1 frameshift mutation, and other molecular abnormalities. Due to the rarity of FGFR3 fusions in prostate cancer, a workup for a second primary cancer was performed, leading to the diagnosis of an otherwise-asymptomatic urothelial carcinoma (UC). Once UC-directed treatment was initiated, the presence of these genetic abnormalities in cfDNA allowed for disease monitoring and early detection of resistance, well before radiographic progression. These findings also uncovered opportunities for targeted therapies against FGFR and BRCA1. Overall, this report highlights the multifaceted utility of longitudinal ctDNA monitoring in early cancer diagnosis, disease prognostication, therapeutic target identification, monitoring of treatment response, and early detection of emergence of resistance.

Genomic alterations associated with pseudoprogression and hyperprogressive disease during anti-PD1 treatment for advanced non-small-cell lung cancer

Introduction

This study aimed to elucidate the relationship between dynamic genomic mutation alteration and pseudoprogression (PsPD)/hyperprogressive disease (HPD) in immunotherapy-treated advanced non-small-cell lung cancer (NSCLC), to provide clinical evidence for identifying and distinguishing between PsPD and HPD.

Method

Patients with advanced NSCLC who were treated with anti-PD1 were enrolled. Whole blood was collected at baseline and post image progression. Serum was separated and sequenced using 425-panel next-generation sequencing analysis (NGS).

Results

NGS revealed that not only single gene mutations were associated with PsPD/HPD before treatment, dynamic monitoring of the whole-blood genome mutation spectrum also varied greatly. Mutational burden, allele frequency%, and relative circulating tumor DNA abundance indicated that the fold change after image progression was much higher in the HPD group.

Discussion

The gene mutation profiles of PsPD and HPD not only differed before treatment, but higher genome mutation spectrum post image progression indicated true disease progression in patients with HPD. This suggests that dynamic whole-genome mutation profile monitoring as NGS can distinguish PsPD from HPD more effectively than single gene detection, providing a novel method for guiding clinical immune treatment.

Enhanced clinical assessment of hematologic malignancies through routine paired tumor and normal sequencing

Genomic profiling of hematologic malignancies has augmented our understanding of variants that contribute to disease pathogenesis and supported development of prognostic models that inform disease management in the clinic. Tumor only sequencing assays are limited in their ability to identify definitive somatic variants, which can lead to ambiguity in clinical reporting and patient management. Here, we describe the MSK-IMPACT Heme cohort, a comprehensive data set of somatic alterations from paired tumor and normal DNA using a hybridization capture-based next generation sequencing platform. We highlight patterns of mutations, copy number alterations, and mutation signatures in a broad set of myeloid and lymphoid neoplasms. We also demonstrate the power of appropriate matching to make definitive somatic calls, including in patients who have undergone allogeneic stem cell transplant. We expect that this resource will further spur research into the pathobiology and clinical utility of clinical sequencing for patients with hematologic neoplasms.

The nexus of dynamic T cell states and immune checkpoint blockade therapy in the periphery and tumor microenvironment

Immune checkpoint blockade (ICB) therapies, that is, using monoclonal antibodies to reinvigorate tumor-reactive, antigen-specific T cells from the inhibitory effects of CTLA-4, PD-1 and PD-L1 immune checkpoints, have revolutionized the therapeutic landscape of modern oncology. However, only a subset of patients can benefit from the ICB therapy. Biomarkers associated with ICB response, resistance and prognosis have been subjected to intensive research in the past decade. Early studies focused on the analysis of tumor specimens and their residing microenvironment. However, biopsies can be challenging to obtain in clinical practice, and do not reflect the dynamic changes of immunological parameters during the ICB therapy. Recent studies have investigated profiles of antigen-specific T cells derived from the peripheral compartment using multi-omics approaches. By tracking the clonotype and diversity of tumor-reactive T cell receptor repertoire, these studies collectively establish that de novo priming of antigen-specific T cells in peripheral blood occurs throughout the course of ICB, whereas preexisting T cells prior to ICB are exhausted to various degrees. Here, we review what is known about ICB-induced T cell phenotypic and functional changes in cancer patients both within the tumor microenvironment and in the peripheral compartment. A better understanding of parameters influencing the response to ICBs will provide rationales for developing novel diagnostics and combinatorial therapeutic strategies to maximize the clinical efficacies of ICB therapies.