Biomarkers For Cancer Immunotherapy Research Articles

Efficacy and safety of chemoimmunotherapy in advanced non-small cell lung cancer patients with antibiotics-induced dysbiosis: a propensity-matched real-world analysis

PurposeThe gut microbiota is hypothesized as a prognostic biomarker for cancer immunotherapy. Antibiotic-induced dysbiosis negatively affects the clinical outcomes of immunotherapy. However, the effect of dysbiosis on the efficacy and safety of Chemoimmunotherapy (chemo-IOs), the frontline standard of care, in advanced non-small cell lung cancer (NSCLC) remains unknown. We aimed to compare the efficacy and safety of chemo-IOs in patients exposed to antibiotics before treatment with those of patients who were not exposed.MethodsWe retrospectively reviewed patients with advanced NSCLC treated with first-line chemo-IOs between 2018 and 2020 at the National Cancer Center Hospital. The patients were divided into two groups: those exposed to antibiotics within 30 days before induction therapy (ABx group) and those did not antibiotics (Non-ABx group). Propensity score matching was used to control for potential confounding factors. Clinical outcomes including progression-free survival (PFS), overall survival (OS), and immune-related adverse events (irAEs) were compared.ResultsOf 201 eligible patients, 21 were in the ABx group, and 42 were in the non-ABx group after propensity score matching. No differences in PFS or OS emerged between the two groups (ABx group vs. Non-ABx group) (PFS:7.0 months vs. 6.4 months, hazard ratio [HR] 0.89; 95% confidence interval [CI], 0.49–1.63, OS:20.4 months vs. 20.1 months, HR 0.87; 95% CI 0.44–1.71). The frequency of irAEs before propensity score matching was similar across any-grade irAEs (39.4% vs. 42.9%) or grade 3 or higher irAEs (9.1% vs. 11.3%).ConclusionAntibiotic-induced dysbiosis may not affect the efficacy of chemo-IOs in patients with advanced NSCLC.

Automated tumor immunophenotyping predicts clinical benefit from anti-PD-L1 immunotherapy.

Cancer immunotherapy has transformed the clinical approach to patients with malignancies, as profound benefits can be seen in a subset of patients. To identify this subset, biomarker analyses increasingly focus on phenotypic and functional evaluation of the tumor microenvironment to determine if density, spatial distribution, and cellular composition of immune cell infiltrates can provide prognostic and/or predictive information. Attempts have been made to develop standardized methods to evaluate immune infiltrates in the routine assessment of certain tumor types; however, broad adoption of this approach in clinical decision-making is still missing. We developed approaches to categorize solid tumors into 'desert', 'excluded', and 'inflamed' types according to the spatial distribution of CD8+ immune effector cells to determine the prognostic and/or predictive implications of such labels. To overcome the limitations of this subjective approach, we incrementally developed four automated analysis pipelines of increasing granularity and complexity for density and pattern assessment of immune effector cells. We show that categorization based on 'manual' observation is predictive for clinical benefit from anti-programmed death ligand 1 therapy in two large cohorts of patients with non-small cell lung cancer or triple-negative breast cancer. For the automated analysis we demonstrate that a combined approach outperforms individual pipelines and successfully relates spatial features to pathologist-based readouts and the patient's response to therapy. Our findings suggest that tumor immunophenotype generated by automated analysis pipelines should be evaluated further as potential predictive biomarkers for cancer immunotherapy. © 2024 The Pathological Society of Great Britain and Ireland.

PD-L1 expression and microsatellite instability (MSI) in cancer of unknown primary site.

Cancer of unknown primary site (CUP) is a heterogeneous group of tumors for which the origin remains unknown. Clinical outcomes might be influenced by regulatory processes in its microenvironment. Microsatellite instability (MSI) is a predictive biomarker for cancer immunotherapy and its status, as well as co-occurrence with PD-L1 expression, is poorly evaluated. We aim to evaluate the expression of PD-L1 and the status of MSI in CUP and their possible associations with clinical-pathological features. The combined positive score (CPS) PD-L1 expression was evaluated by immunohistochemistry. MSI status was assessed using a hexa-plex marker panel by polymerase chain reaction followed by fragment analysis. Among the 166 cases, MSI analysis was conclusive in 120, with two cases being MSI positive (1.6%). PD-L1 expression was positive in 18.3% of 109 feasible cases. PD-L1 expression was significantly associated with non-visceral metastasis and a dominance of nodal metastasis. The median overall survival (mOS) was 3.7 (95% CI 1.6-5.8) months and patients who expressed PD-L1 achieved a better mOS compared to those who did not express PD-L1 (18.7 versus 3.0 months, p-value: < .001). ECOG-PS equal to or more than two and PD-L1 expression were independent prognostic factors in multivariate analysis (2.37 and 0.42, respectively). PD-L1 is expressed in a subset (1/5) of patients with CUP and associated with improved overall survival, while MSI is a rare event. There is a need to explore better the tumor microenvironment as well as the role of immunotherapy to change such a bad clinical outcome.

Abstract 4220: Combined light sheet and multispectral imaging facilitates the detection of tumor-associated tertiary lymphoid structures in the KP NSCLC model

Abstract Tertiary lymphoid structures (TLS) have recently emerged as a predictive biomarker in cancer immunotherapy. Their consideration in preclinical drug development is impeded by rare and transient appearance and random distribution, making them difficult to analyze with conventional sampling methods. We applied whole-organ tissue clearing and 3D staining of B and T cell clusters to comprehensively identify TLS in a KP GEMM of NSCLC using 3D Light Sheet Fluorescence Microscopy (3D LSFM). To further investigate cellular composition of TLS we performed 3D LSFM-educated sectioning of relevant ROIs and cyclic immunofluorescence of the same samples. 3D LSFM facilitated correlation of tumor features and location with T cell infiltration as well as the analysis of number, size and location of TLS. The majority of TLS were located in proximity to bronchi instead of intratumorally. LSFM-guided multiplex immunofluorescence revealed further details on cellular composition and maturation status of TLS. This combination of 3D and 2D imaging modalities offers a holistic approach for the identification of TLS in whole murine tumors or organs. The technology could help studying effects of immunotherapy on de novo formation or maturation of TLS. Citation Format: Nils O'Brien, Birte Appelt, Marie-Lena Moerbitz, Joerg P. Mueller, Frank Herting, Pablo Umaña, Claudio Murgia, Sara Colombetti, Thomas Pöschinger. Combined light sheet and multispectral imaging facilitates the detection of tumor-associated tertiary lymphoid structures in the KP NSCLC model [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4220.

Navigating PRKCSH's impact on cancer: from N-linked glycosylation to death pathway and anti-tumor immunity.

PRKCSH, also known as Glucosidase II beta subunit (GluIIβ), is a crucial component of the endoplasmic reticulum (ER) quality control system for N-linked glycosylation, essential for identifying and eliminating misfolded proteins. Glucosidase II consists of the catalytic alpha subunit (GluIIα) and the regulatory beta subunit (GluIIβ), ensuring proper protein folding and release from the ER. The induction of PRKCSH in cancer and its interaction with various cellular components suggest broader roles beyond its previously known functions. Mutations in the PRKCSH gene are linked to autosomal dominant polycystic liver disease (ADPLD). Alternative splicing generates distinct PRKCSH isoforms, which can influence processes like epithelial-mesenchymal transition (EMT) and the proliferation of lung cancer cells. PRKCSH's involvement in cancer is multifaceted, impacting cell growth, metastasis, and response to growth factors. Additionally, PRKCSH orchestrates cell death programs, affecting both autophagy and apoptosis. Its role in facilitating N-linked glycoprotein release from the ER is hypothesized to assist cancer cells in managing increased demand and ER stress. Moreover, PRKCSH modulates anti-tumor immunity, with its suppression augmenting NK cell and T cell activity, promising enhanced cancer therapy. PRKCSH's diverse functions, including regulation of IGF1R and IRE1α, implicate it as a therapeutic target and biomarker in cancer immunotherapy. However, targeting its glucosidase II activity alone may not fully counteract its effects, suggesting broader mechanisms in cancer development. Further investigations are needed to elucidate PRKCSH's precise role and validate its therapeutic potential in cancer treatment.

Comprehensive analysis of fibroblast activation protein expression across 23 tumor indications: insights for biomarker development in cancer immunotherapies.

Fibroblast activation protein (FAP) is predominantly upregulated in various tumor microenvironments and scarcely expressed in normal tissues. We analyzed FAP across 1216 tissue samples covering 23 tumor types and 70 subtypes. Elevated FAP levels were notable in breast, pancreatic, esophageal, and lung cancers. Using immunohistochemistry and RNAseq, a correlation between FAP gene and protein expression was found. Evaluating FAP's clinical significance, we assessed 29 cohorts from 12 clinical trials, including both mono and combination therapies with the PD-L1 inhibitor atezolizumab and chemotherapy. A trend links higher FAP expression to poorer prognosis, particularly in RCC, across both treatment arms. However, four cohorts showed improved survival with high FAP, while in four others, FAP had no apparent survival impact. Our results emphasize FAP's multifaceted role in therapy response, suggesting its potential as a cancer immunotherapy biomarker.

Preliminary exploration of the potential biological functions and prognosis values of RAB4B in pan-cancer combing with experimental validation in BLCA.

Ras-related protein Rab-4B (RAB4B), a small GTPase in the RAS superfamily, is involved in glucose homeostasis, synaptic homeostasis, adaptive immunity, and other processes. RAB4B has also been implicated in tumorigenesis, and its dysregulation has been linked to cancer in multiple organs. However, the potential role of RAB4B in human pan-cancers remains unknown, and whether RAB4B is a predictive biomarker for cancer immunotherapy is yet to be explored. In order to investigate the potential for RAB4B as a therapeutic agent in human pan-cancers and its predictive properties, firstly, relevant data were downloaded from pan-cancers databases. Using the RAB4B expression as a parameter, an analysis was performed. The next step was to investigate how RAB4B relates to overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI). Moreover, we performed an analysis of the relationship between RAB4B and tumor mutational burden (TMB), microsatellite instability (MSI), and tumor microenvironment (TME). Besides, the tumor immune dysfunction and exclusion (TIDE) algorithm was applied to evaluate the efficacy of RAB4B as a potential biomarker for cancer immunotherapy. A final analysis was performed on RAB4B in relation to immune-related genes and pathways. Results reflected that RAB4B expression was different between tumors and normal tissues. RAB4B not only positively or negatively correlated with survival indicators, but also with clinical characteristics. In addition, RAB4B positively or negatively correlated with TMB, MSI, and TME. The TIDE algorithm revealed that RAB4B was positively or negatively associated with immune checkpoint blockade. The outcome of gene set enrichment analysis (GSEA) suggested that RAB4B positively regulated biological processes and immune cell-related pathways in most cancers. According to the research results, we come to the conclusion that RAB4B as a biomarker for tumor immunotherapy, RAB4B facilitates the prediction of pan-cancers prognosis.

MSIsensor-RNA: Microsatellite Instability Detection for Bulk and Single-cell Gene Expression Data

Abstract Microsatellite instability (MSI) is an indispensable biomarker in cancer immunotherapy. Currently, MSI scoring methods by high-throughput omics methods have gained popularity and demonstrated better performance than the gold standard method for MSI detection. However, the MSI detection method on expression data, especially single-cell expression data, is still lacking, limiting the scope of clinical application and prohibiting the investigation of MSI at a single-cell level. Herein, we developed MSIsensor-RNA, an accurate, robust, adaptable, and standalone software to detect MSI status based on expression values of MSI-associated genes. We demonstrated the favorable performance and promise of MSIsensor-RNA in both bulk and single-cell gene expression data in multiplatform technologies including RNA sequencing (RNA-seq), microarray, and single-cell RNA-seq. MSIsensor-RNA is a versatile, efficient, and robust method for MSI status detection from both bulk and single-cell gene expression data in clinical studies and applications. MSIsensor-RNA is available at https://github.com/xjtu-omics/msisensor-rna.

Abstract B016: Developing diagnostic tools via mutational spectra analysis and multiomic plasma profiling from liquid biopsies to identify potential signatures in cancer in Trinidad and Tobago

Abstract Cancer, especially lung cancer is a leading cause of nosocomial deaths worldwide. Non-small cell lung cancer (NSCLC) has a five-year survival rate of only 24%. Early diagnoses markedly improves survival with personalized cancer therapies using non-invasive techniques for asymptomatic detection of mutational spectrum-related by genotyping NSCLC patients, even prior to symptoms. Analysis of conformational change in proteins due to mutations in oncogenes allow for mutation-specific treatment with specialized cancer drugs. In addition, tumor mutational burden (TMB) is a promising predictive biomarker for cancer immunotherapy as high TMB patients respond better to immune checkpoint inhibitors cancer drugs. Treatment planning for non-small cell lung cancer generally requires testing for EGFR, ALK, ROS1, BRAF, MET, RET and KRAS gene alterations or whole genome analysis to assess TMB. The Caribbean region remains disadvantaged by the lack of available genetic testing mainly due to accessibility. We propose the genotyping of 30 stage III-IV NSCLC patients via next-generation sequencing (NGS) to improve personalized therapies. Through the analysis of tumor-specific alterations amongst a complete mutation spectrum analysis, including single nucleotide variants (SNVs), insertions, deletions, copy number variations (CNVs), and methylation alterations, we would generate data to be used as an accurate form of cancer genotyping for diagnostic purposes. We intend to include these genes as biomarkers in a mutational spectrum analysis, to be collated into a predictive DNA assay to be used for the first time as a diagnostic/prognostic tool in a medically underserved community. We intend to also identify TMB-high patients without cost-prohibitive whole genome sequencing by focusing on DNA damage repair (DDR) genes. There is an increasing utilization of agnostic testing which involves the analysis of all potentially actionable genes across all tumor and cancer types. The invention of genomic-tailored specialized cancer treatments has resulted in a spectacular improvement in disease outcomes for a significant portion of cancer patients, which we hope to offer to improve clinical outcomes and prognosis in the racially diverse population of Trinidad and Tobago. Citation Format: Nicole Ramlachan, Samuel M. West. Developing diagnostic tools via mutational spectra analysis and multiomic plasma profiling from liquid biopsies to identify potential signatures in cancer in Trinidad and Tobago [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: DNA Damage Repair: From Basic Science to Future Clinical Application; 2024 Jan 9-11; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2024;84(1 Suppl):Abstract nr B016.

Plasma cell-free DNA as a sensitive biomarker for multi-cancer detection and immunotherapy outcomes prediction

BackgroundCell-free DNA (cfDNA) has shown promise in detecting various cancers, but the diagnostic performance of cfDNA end motifs for multiple cancer types requires verification. This study aimed to assess the utility of cfDNA end motifs for multi-cancer detection.MethodsThis study included 206 participants: 106 individuals with cancer, representing 20 cancer types, and 100 healthy individuals. The participants were divided into training and testing cohorts. All plasma cfDNA samples were profiled by whole-genome sequencing. A random forest model was constructed using cfDNA 4 bp-end-motif profiles to predict cancer in the training cohort, and its performance was evaluated in the testing cohort. Additionally, a separate random forest model was developed to predict immunotherapy responses.ResultsIn the training cohort, the model based on 4 bp-end-motif profiles achieved an AUC of 0.962 (95% CI 0.936–0.987). The AUC in the testing cohort was 0.983 (95% CI 0.960–1.000). The model also maintained excellent predictive ability in different tumor sub-cohorts, including lung cancer (AUC 0.918, 95% CI 0.862–0.974), gastrointestinal cancer (AUC 0.966, 95% CI 0.938–0.993), and other cancer cohort (AUC 0.859, 95% CI 0.776–0.942). Moreover, the model utilizing 4 bp-end-motif profiles exhibited sensitivity in identifying responders to immunotherapy (AUC 0.784, 95% CI 0.609–0.960).ConclusionThe model based on 4 bp-end-motif profiles demonstrates superior sensitivity in multi-cancer detection. Detection of 4 bp-end-motif profiles may serve as potential predictive biomarkers for cancer immunotherapy.

Progresses in biomarkers for cancer immunotherapy.

Currently, checkpoint inhibitor-based immunotherapy has emerged as prevailing treatment modality for diverse cancers. However, immunotherapy as a first-line therapy has not consistently yielded durable responses. Moreover, the risk of immune-related adverse events increases with combination regimens. Thus, the development of predictive biomarkers is needed to optimize individuals benefit, minimize risk of toxicities, and guide combination approaches. The greatest focus has been on tumor programmed cell death-ligand 1 (PD-L1), microsatellite instability (MSI), and tumor mutational burden (TMB). However, there remains a subject of debate due to thresholds variability and significant heterogeneity. Major unmet challenges in immunotherapy are the discovery and validation of predictive biomarkers. Here, we show the status of tumor PD-L1, MSI, TMB, and emerging data on novel biomarker strategies with oncogenic signaling and epigenetic regulation. Considering the exploration of peripheral and intestinal immunity has served as noninvasive alternative in predicting immunotherapy, this review also summarizes current data in systemic immunity, encompassing solute PD-L1 and TMB, circulating tumor DNA and infiltrating lymphocytes, routine emerging inflammatory markers and cytokines, as well as gut microbiota. This review provides up-to-date information on the evolving field of currently available biomarkers in predicting immunotherapy. Future exploration of novel biomarkers is warranted.

CoraL: interpretable contrastive meta-learning for the prediction of cancer-associated ncRNA-encoded small peptides.

NcRNA-encoded small peptides (ncPEPs) have recently emerged as promising targets and biomarkers for cancer immunotherapy. Therefore, identifying cancer-associated ncPEPs is crucial for cancer research. In this work, we propose CoraL, a novel supervised contrastive meta-learning framework for predicting cancer-associated ncPEPs. Specifically, the proposed meta-learning strategy enables our model to learn meta-knowledge from different types of peptides and train a promising predictive model even with few labeled samples. The results show that our model is capable of making high-confidence predictions on unseen cancer biomarkers with only five samples, potentially accelerating the discovery of novel cancer biomarkers for immunotherapy. Moreover, our approach remarkably outperforms existing deep learning models on 15 cancer-associated ncPEPs datasets, demonstrating its effectiveness and robustness. Interestingly, our model exhibits outstanding performance when extended for the identification of short open reading frames derived from ncPEPs, demonstrating the strong prediction ability of CoraL at the transcriptome level. Importantly, our feature interpretation analysis discovers unique sequential patterns as the fingerprint for each cancer-associated ncPEPs, revealing the relationship among certain cancer biomarkers that are validated by relevant literature and motif comparison. Overall, we expect CoraL to be a useful tool to decipher the pathogenesis of cancer and provide valuable information for cancer research. The dataset and source code of our proposed method can be found at https://github.com/Johnsunnn/CoraL.

A near-infrared fluorescence-enhancing plasmonic biosensing microarray identifies soluble PD-L1 and ICAM-1 as predictive checkpoint biomarkers for cancer immunotherapy

Sensitive and accurate biomarker-driven assay guidance has been widely adopted to identify responsive patients for immune checkpoint blockade (ICB) therapy to impede disease progression and extend survival. However, most current assays are invasive, requiring surgical pathology specimens and only informing monochronic information. Here, we report a multiplexed enhanced fluorescence microarray immunoassay (eFMIA) based on a nanostructured gold nanoisland substrate (AuNIS), which macroscopically amplifies near-infrared fluorescence (NIRF) of a structurally symmetric IRDye78 fluorophore by over two orders of magnitude of 202.6-fold. Aided by non-contact piezo-driven micro-dispensing (PDMD), eFMIA simultaneously and semi-quantitatively detected intracellular and secreted programmed death-ligand 1 (PD-L1) and intercellular adhesion molecule-1 (ICAM-1) in human nasopharyngeal carcinoma (NPC) cells. The assay performance was superior to fluorescence immunoassays (FIA) and enzyme-linked immunosorbent assays (ELISA), with lower detection limits. Using eFMIA, we found significantly differential levels of soluble PD-L1 (sPD-L1) and sICAM-1 in the sera of 28 cancer patients, with different clinical outcomes following anti-PD-1 ICB therapy. With a well-characterized mechanism, the high-performance plasmonic multiplexed assay with the composite biomarkers may be a valuable tool to assist clinicians with decision-making and patient stratification to afford predictive ICB therapy responses.

Small Leucine-Rich Proteoglycan PODNL1 Identified as a Potential Tumor Matrix-Mediated Biomarker for Prognosis and Immunotherapy in a Pan-Cancer Setting.

The podocan-like protein 1 (PODNL1), an important member of the small leucine-rich proteoglycans (SLRP) family, is a crucial component of the tumor microenvironment (TME). But its prognostic values and the role in the TME have not been systematically estimated in a pan-cancer setting. Targeting PODNL1, a systematic exploration into the TCGA datasets, reconciling with the analyses of single-cell transcriptomes and immunotherapeutic cohorts in cancers, and validation by tissue microarray-based multiplex immunofluorescence staining was performed. PODNL1 was significantly correlated with the poor prognosis and immunotherapeutic responses in various cancers. In-depth demonstration of molecular mechanisms indicated that PODNL1 expressions were notably positively correlated with cancer-associated fibroblast (CAF) infiltration levels in 33 types of cancers. It also positively correlated with the pan-fibroblast TGF-β response signature score, and the hallmarks including TGF-β, TNF-α, inflammatory response, apical junction, epithelial-mesenchymal transition and hedgehog in pan-cancer. Furthermore, high PODNL1 expressions were positively related with the regulation of tumor-promoting TGF-β signaling through downregulating SMAD2/3:4 heterotrimer regulations transcription and up-regulating the pathway restricted SMAD protein phosphorylation. Single-cell transcriptome analyses and immunofluorescence validations indicated that PODNL1 was predominantly expressed in the cancer cells and CAFs in various cancers. Additionally, the heterogeneity of cancer genotype-phenotype cross-talking was also observed associated with PODNL1. Our systematic study indicates that PODNL1 plays an important role in the complex regulation network of tumor progression, and lays a foundation for further exploration to develop PODNL1 as a valuable matrix-mediated biomarker for cancer immunotherapy and prognosis in a pan-cancer setting.

Indoleamine 2,3-Dioxygenase (IDO) Activity: A Perspective Biomarker for Laboratory Determination in Tumor Immunotherapy.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a heme enzyme involved in catalyzing the conversion of tryptophan (Trp) into kynurenine (Kyn) at the first rate-limiting step in the kynurenine pathway of L-tryptophan metabolism. It has been found to be involved in several biological functions such as aging, immune microorganism, neurodegenerative and infectious diseases, and cancer. IDO1 plays an important role in immune tolerance by depleting tryptophan in the tumor microenvironment and inhibiting the proliferation of effector T cells, which makes it an important emerging biomarker for cancer immunotherapy. Therefore, the research and development of IDO1 inhibitors are of great importance for tumor therapy. Of interest, IDO activity assays are of great value in the screening and evaluation of inhibitors. Herein, we mainly review the biological functions of IDO1, immune regulation, key signaling molecules in the response pathway, and the development of IDO1 inhibitors in clinical trials. Furthermore, this review provides a comprehensive overview and, in particular, a discussion of currently available IDO activity assays for use in the evaluation of IDO inhibitors in human blood. We believe that the IDO activity is a promising biomarker for the immune escape and laboratory evaluation of tumor immunotherapy.

PTPRD/PTPRT mutation correlates to treatment outcomes of immunotherapy and immune landscape in pan-cancers.

PTPRD and PTPRT are phosphatases of the JAK-STAT pathway related to immunotherapy. However, the role and mechanism of PTPRD and PTPRT mutations in multiple cancers remains unclear. Clinical data and PTPRD/PTPRT mutation information from 12 cohorts were collected and classified as a discovery cohort and three validation cohorts. The association between PTPRD/PTPRT mutations and immunotherapeutic efficacy was analyzed. Then, the association between PTPRD/PTPRT mutation and immune profiles was analyzed using The Cancer Genome Atlas (TCGA) cohort. A total of 2,392 patients across 20 cancer types were included in this study. Our results showed that patients harboring PTPRD/PTPRT mutation, especially co-mutations, had a significantly elevated response rate to immunotherapy in multiple cancers. Patients with PTPRD/PTPRT mutation had a higher objective response rate (ORR) (P=0.002), longer overall survival (OS) (P=0.005) and progression-free survival (PFS) (P=0.038). Importantly, the above findings were further verified in validation cohorts. In addition, we found that the PTPRD/PTPRT co-mutations (co-mut) subgroup exhibited an immune-activated phenotype, the wild-type subgroup tended to have an immune-desert phenotype, and the uni-mutation (uni-mut) subgroup might have an immune-mixed phenotype. Our further analyses suggested that combining programmed cell death ligand 1 (PD-L1) expression and PTPRD/PTPRT mutation can be used to screen patients who may benefit from immunotherapy. PTPRD/PTPRT mutation could serve as a potential predictive biomarker for cancer immunotherapy.

Gut OncoMicrobiome Signatures (GOMS) as next-generation biomarkers for cancer immunotherapy.

Oncogenesis is associated with intestinal dysbiosis, and stool shotgun metagenomic sequencing in individuals with this condition might constitute a non-invasive approach for the early diagnosis of several cancer types. The prognostic relevance of antibiotic intake and gut microbiota composition urged investigators to develop tools for the detection of intestinal dysbiosis to enable patient stratification and microbiota-centred clinical interventions. Moreover, since the advent of immune-checkpoint inhibitors (ICIs) in oncology, the identification of biomarkers for predicting their efficacy before starting treatment has been an unmet medical need. Many previous studies addressing this question, including a meta-analysis described herein, have led to the description of Gut OncoMicrobiome Signatures (GOMS). In this Review, we discuss how patients with cancer across various subtypes share several GOMS with individuals with seemingly unrelated chronic inflammatory disorders who, in turn, tend to have GOMS different from those of healthy individuals. We discuss findings from the aforementioned meta-analysis of GOMS patterns associated with clinical benefit from or resistance to ICIs across different cancer types (in 808 patients), with a focus on metabolic and immunological surrogate markers of intestinal dysbiosis, and propose practical guidelines to incorporate GOMS in decision-making for prospective clinical trials in immuno-oncology.

Genomic characterization of MSI-H and TMB in gastrointestinal cancer.

e15524 Background: Microsatellite instability (MSI) is a molecular marker of a deficient in mismatch repair (MMR) system. It is one of the main hallmarks in colorectal cancer (CRC) and gastric cancer (GC), occurring in 15% and 18% of CRC and GC respectively. Mutations occur in MMR system genes will impair DNA mismatch recognition and cause accumulation of mutations in DNA microsatellite regions. As a result, microsatellite instability-high (MSI-H) patients often possess an abnormally high number of somatic mutations and would lead to high tumour mutation burden (TMB), which is a prevalent biomarker in cancer immunotherapy. Here we analysed the genomic landscape of 974 gastrointestinal cancer patients to provide new insights on the relationship between MSI, TMB and other genetic mutation characteristics. Methods: Panel sequencing targeting 680 cancer-related genes were performed on patients with colonrectal cancer (n = 569), gastric cancer (n = 375), intestinal cancer (n = 25) and oesophagal cancer (n = 5) on either fresh tumour tissue or formalin-fixed paraffin embedded tumor DNA. Genomic alterations including single nucleotide variations, short insertions and deletions, copy number variations, tumour mutation burden and micro-satellite instability were analysed. Results: Among the 974 patients, 86 patients (8.83%) were classified as MSI-H based on evaluation of 117 MMR-related loci, while rest of the patients (n = 888, 91.2%) were classified as microsatelite stable (MSS). In MSI-H cohort, 68.6% of the patients were classified as TMB-H with a TMB level higher than 10 Muts/Mb, while in MSS cohort, only 3.71% of the patients were classified as TMB-H. The TMB value of MSI-H cohort is also significantly higher than the MSS cohort (p &lt; 0.0001, two-tailed T-test). Meanwhile, we discovered that proportion of patients with mutated lysine methyltransferase family gene KMT2D (54.65% vs 7.17%, p &lt; 0.0001), KMT2B (48.84% vs 3.25%, p &lt; 0.0001) and KMT2C (44.19% vs 7.17%, p &lt; 0.0001) showed significant difference between MSI-H and MSS cohorts (Two-sided Fisher’s exact test). Conclusions: This study demonstrated that MSI-H is highly correlated with TMB-H, providing a new insight of evaluating gastrointestinal cancer treatment on MSI-H patients. The study also revealed novel MSI-H genetic mutation landscape for KMT gene family. Concurrent with recent researches, this study further boosts the potential of KMT genes to be used as a biomarker in both diagnosis and immunotherapy treatment.

Serum soluble MAdCAM-1: A new biomarker for cancer immunotherapy.

4548 Background: Antibiotics (ATB) deviate the gut taxonomic microbiota composition and have a deleterious impact on survival in ICI-treated pts. ATB downregulate the ileal mucosal addressin cell adhesion molecule-1 (MAdCAM-1), leading to the recirculation of immunosuppressive enterotropic T cells into the tumor and ICI resistance. Here, we aimed to assess the prognostic impact of MAdCAM-1 in ICI-treated mRCC pts. Methods: The GETUG-AFU 26 NIVOREN phase II trial (NCT 0301335) is a multicentric study that assessed the activity and safety of Nivolumab in pts with clear cell mRCC after anti-angiogenic therapy. We measured serum soluble MAdCAM-1 (sMAdCAM-1) levels (correlating ileal MAdCAM-1 transcripts) using Human Luminex Discovery Assay in the available plasma. Progression-free survival (PFS), overall survival (OS) and clinical benefit rate (CBR) were assessed using sMAdCAM-1 median as a cut off value (high if &gt;median and low if &lt;median). Multivariate Cox analysis adjusted for established risk factors: ATB, gender, age, international Metastatic RCC Database Consortium (IMDC) score, number of previous lines, hypoalbuminemia, and brain, bone and liver metastasis. Two independent cohorts of metastatic lung and bladder cancer patients validated the data. Results: Overall, 212 pts were included. Median age was 64 years (22-87), and pts were mostly male (82%). ATB users had lower levels of sMadCAM-1. Low sMadCAM-1 pts had diminished OS compared to high sMadCAM-1 pts [HR 2.97 (95%CI 1.99-4.44), p&lt;.0001]: 13.3 (95%CI 9.8-14.9; 72/106) versus 25.3 (95%CI 24.1-NR; 36/106) months. Also, low sMadCAM-1 pts had diminished PFS [HR 1.92 (1.43-2.57), p&lt;.0001]: 2.6 (95%CI 2.4-2.8; 99/106) versus 5.2 (95%CI 4.6-5.7; 86/106) months. Interestingly, sMAdCAM-1 was independently associated with OS [HR 2.40 (1.52-3.80), p=0.0002] and PFS [HR 1.55 (1.13-2.13), p=0.0071] in multivariate analysis. Low sMadCAM-1 pts had lower CBR (37% versus 63%, p=0.0004). Serum sMAdCAM-1 also predicted OS in 381 ICI-treated patients with lung and bladder cancer. Conclusions: Low sMAdCAM-1 is associated with ATB intake, ATB-independent gut dysbiosis and worse outcomes, in ICI-treated pts with metastatic lung, bladder and RCC cancer. ELISA determination of sMAdCAM-1 might guide the selection of patients amenable to microbiota-centered interventions, such as Akkermansia sp., and fecal microbiota transplantation. Clinical trial information: NCT0301335 .

Association of ctDNA tumor fraction with survival in advanced non-small cell lung cancer (NSCLC) treated with maintenance durvalumab in the UNICANCER SAFIR02-Lung/IFCT1301 trial.

2516 Background: ctDNA shed is a promising biomarker for cancer immunotherapy, with patients (pts) having higher concentration of plasma ctDNA being reported to have poorer outcome. Its role in the maintenance setting with immune checkpoint inhibitors remains unexplored. In SAFIR02-Lung, advanced NSCLC pts were enrolled to receive a platinum-based chemotherapy. After 4 cycles, if stable or in response, pts with no targetable alterations were oriented to the immunotherapy sub-study and randomized between maintenance durvalumab or Standard of Care (SoC) (PMID 35802649). Durvalumab prolonged survival only in the PD-L1 ≥ 1% subgroup. Here we explored Tumor Fraction (TF) as determined by Low-Pass Whole Genome Sequencing as a biomarker for immunotherapy irrespective of PD-L1. Methods: SAFIR02-Lung (NCT02117167) is a multicentric, randomized phase 2 clinical trial. Plasma samples were obtained at randomization, just before maintenance treatment initiation. DNA was extracted using the Maxwell RSC ccfDNA Plasma Kit (Promega, AS1840). Sequencing libraries were prepared using the Low Input SureSelectXT protocol (Agilent, G9916A). Pooled libraries were sequenced on a NovaSeq 6000 platform (Illumina) as 2 × 150 bp paired-end reads (NovaSeq 6000 SP Reagent Kit v1.5). Genomic copy number aberrations and TF were investigated using the ichorCNA (V0.2.0) tool. TF ≥ 2% was considered positive. For the survival analyses, a landmark approach was performed, by considering the randomization date as the landmark time. Progression Free Survival (PFS) was the primary endpoint, defined as the time from randomization until the date of objective radiological disease progression, clinical progression or death. The secondary endpoint was Overall Survival (OS). Results: 50 out of 121 plasma samples from pts randomized to durvalumab were analyzed for the feasibility part. 34 pts (68%) were &lt; 65 years, 33 (66%) were male. PD-L1 expression was available for 18 pts and 39% of them had PD-L1 ≥ 1%. Median TF was 1.1%, 8 pts (16%) had a TF ≥ 2%, ranging from 2.2% to 23.3%. TF at randomization was marginally correlated with the presence of liver metastases (p 0.063) and with the sum of target lesions (p 0.081). No significant correlation was observed with PD-L1 positivity. Pts with TF ≥ 2% had lower median PFS 1.7months (m) (95% CI 1.2 – 4.2) vs 5.8m (95% CI 2.9 – 7.5) for those with TF &lt; 2%, p 0.0003. Similarly, median OS was lower for pts with TF &gt; 2% 10.4m (95% CI 4.2 – 18.7) vs 25.9m (95% CI 18.2 – NR) for those with TF &lt; 2%, p 0.0002. Data will be presented on the whole cohort, including control group receiving SoC, to discriminate between a prognostic or a predictive value of TF. Conclusions: TF was positive in 16% of pts randomized to durvalumab in the SAFIR02-Lung trial. This population seems to have a limited benefit from maintenance durvalumab after induction chemotherapy. Clinical trial information: NCT02117167 .