257 Development of a diagnostic platform which matches therapies to the tumor microenvironment dominant biology

2020 ◽  
Vol 8 (Suppl 3) ◽  
pp. A280-A280
Author(s):  
Kristen Strand-Tibbitts
Keyword(s):  
Tumor Microenvironment ◽  
Genomic Stability ◽  
Standard Of Care ◽  
Tumor Type ◽  
Biological Processes ◽  
Tumor Mutation Burden ◽  
Gene Signatures ◽  
Mutation Burden ◽  
Check Point Inhibitors ◽  
Exploratory Data

BackgroundTumor microenvironment (TME)-targeting agents such as anti-angiogenic therapies and check-point inhibitors (CPIs), have shown both promise and variability in effectiveness depending on the tumor type. For immune-targeting agents like CPIs, efforts to identify features or biomarkers that predispose responding patients include but are not limited to genomic stability, tumor mutation burden, and PD-L1 expression. Oncologie is developing a RNA-based platform that identifies subsets of patients based on multiple aspects of the biological processes (dominant biology) existing within the tumor microenvironment.MethodsRNA data from publicly available sources including microarray, RNASeq exome and whole RNA were analyzed with respect to gene signatures that describe four different microenvironmental phenotypes. Phenotypes were then evaluated for relationships to clinical efficacy endpoints. From these RNA signatures and driven by machine learning methodologies, drug-specific algorithms were developed and applied to retrospectively to clinical data. Comparative analyses were explored between gene signatures, commonly used biomarkers (eg. presence of microsatellite DNA, expression levels of PD-L1, etc) and within-patient metadata to better understand better how this approach can be utilized in prospective clinical studies.ResultsAttributes in RNA expression identified using Oncologie’s platform have retrospectively characterized responders to CPIs or anti-angiogenic drugs, demonstrating a relationship between clinical response and biomarker positive and negative patient populations. Exploratory data summarizing the use of the this platform demonstrates its utility for enriching response to both immune- and angiogenesis-targeting drugs. Relative expression changes between archival and fresh biopsies demonstrate changes in the TME with time and/or following targeted therapy. Lastly, cross-tumor comparisons support a tumor-agnostic utility of this approach. Detailed comparisons of this biomarker approach relative to other available biomarkers will be presented for standard of care drugs and those in the Oncologie pipeline based on retrospective analyses.ConclusionsRNA based descriptors of biology may be a useful approach to enrich for response to targeted therapies whose mechanism of action is to modify the TME biology.

scholarly journals m6A Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Mengyu Sun ◽  
Meng Xie ◽  
Tongyue Zhang ◽  
Yijun Wang ◽  
Wenjie Huang ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Tumor Microenvironment ◽  
Clustering Algorithm ◽  
Immune Cell ◽  
Biological Processes ◽  
Consensus Clustering ◽  
Tumor Mutation Burden ◽  
Immune Infiltration ◽  
Signature Genes ◽  
Mutation Burden

Recent studies have shown that RNA N6-methyladenosine (m6A) modification plays an important part in tumorigenesis and immune-related biological processes. However, the comprehensive landscape of immune cell infiltration characteristics in the tumor microenvironment (TME) mediated by m6A methylation modification in pancreatic cancer has not yet been elucidated. Based on consensus clustering algorithm, we identified two m6A modification subtypes and then determined two m6A-related gene subtypes among 434 pancreatic cancer samples. The TME characteristics of the identified gene subtypes were highly consistent with the immune-hot phenotype and the immune-cold phenotype respectively. According to the m6A score extracted from the m6A-related signature genes, patients can be divided into high and low m6A score groups. The low score group displayed a better prognosis and relatively strong immune infiltration. Further analysis showed that low m6A score correlated with lower tumor mutation burden and PD-L1 expression, and indicated a better response to immunotherapy. In general, m6A methylation modification is closely related to the diversity and complexity of immune infiltration in TME. Evaluating the m6A modification pattern and immune infiltration characteristics of individual tumors can help deepen our understanding of the tumor microenvironment landscape and promote a more effective clinical practice of immunotherapy.

FoundationOne as a relevant tool for comprehensive genomic profiling and assessment of tumor mutation burden in the era of precision oncology in India.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e23096-e23096
Author(s):  
Amit Verma ◽  
Nitesh Rohatgi ◽  
Pramod Kumar Julka ◽  
Meenu Walia ◽  
Ankur Bahl ◽  
...  
Keyword(s):  
Tyrosine Kinases ◽  
Mutation Frequency ◽  
Unknown Primary ◽  
Precision Oncology ◽  
Tumor Type ◽  
Genomic Profiling ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Comprehensive Genomic Profiling ◽  
Tumor Types

e23096 Background: Comprehensive genomic profiling (CGP) is gaining acceptability globally, but clinical experience in developing countries like India is limited. CGP identifies genomic alterations (GA), with tumor mutation burden (TMB) and microsatellite status (MSI), revealing therapeutic options such as targeted inhibitors and immunotherapies. We sought to evaluate the mutation frequency and actionability across tumors. Methods: Metastatic and/or refractory patients (referred to Personalized Cancer Medicine Clinic) underwent CGP analysis, including calculation of TMB and MSI, using a targeted NGS panel (FoundationOne, 53 samples; FoundationOne Heme, 4 samples). This panel detects all relevant classes of GA: base substitutions, small indels, rearrangements and copy number changes. Mutation frequencies were compared with the larger Foundation database. TMB status was reported as low (≤5 mutations/Mb), intermediate (6-19 mut/Mb) or high (≥20 mut/Mb). Results: The most common tumor types were lung (23%), breast (14%) and sarcoma (12%); other tumor types, including unknown primary constituted the rest (51%). Most samples were from metastatic sites (60%). Oncogenic GA were found in 131 genes across all tumor subtypes and affected major pathways: apoptosis/cell cycle (31%), PI3K (14%), transcriptional regulation (13%), and receptor tyrosine kinases (10%). Among these GA, 38 were considered actionable and were distributed across 43 (75%) samples. Therapies with FDA approval for the tumor type analyzed were indicated for 18 samples; an additional 25 samples had GA associated with therapies FDA approved for another indication. More than 1 actionable GA was identified in 24/43 (56%). TMB status was low in 36 (63%), intermediate in 19 (33%) and high in 2 (3.5%). High TMB status correlated with high MSI status (p < 0.001). Trend observed in the mutation frequency was comparable with the larger Foundation database. Conclusions: This is the first study in India showing CGP identified actionable targets associated with FDA approved therapies in approx. 32% of cases. TMB status identified 2/57 samples with high mutation burden for whom immunotherapy might be relevant.

scholarly journals Molecular Characterization of the Clinical and Tumor Immune Microenvironment Signature of 5-methylcytosine-Related Regulators in non-small Cell Lung Cancer

2021 ◽  
Vol 9 ◽  
Author(s):  
Taisheng Liu ◽  
Liyi Guo ◽  
Guihong Liu ◽  
Xiaoshan Hu ◽  
Xiaoning Li ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Microenvironment ◽  
Immune Cell ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Check Point ◽  
Clinical Prognosis ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Immune Check Point Inhibitor

Background: DNA methylation is an important epigenetic modification, among which 5-methylcytosine methylation (5mC) is generally associated with tumorigenesis. Nonetheless, the potential roles of 5mC regulators in the tumor microenvironment (TME) remain unclear.Methods: The 5mC modification patterns of 1,374 lung adenocarcinoma samples were analyzed systematically. The correlation between the 5mC modification and tumor microenvironment cell infiltration was further assessed. The 5mCscore was developed to evaluate tumor mutation burden, immune check-point inhibitor response, and the clinical prognosis of individual tumors.Results: Three 5mC modification patterns were established based on the clinical characteristics of 21 5mC regulators. According to the differential expression of 5mC regulators, three distinct 5mC gene cluster were also identified, which showed distinct TME immune cell infiltration patterns and clinical prognoses. The 5mCscore was constructed to evaluate the tumor mutation burden, immune check-point inhibitor response, and prognosis characteristics. We found that patients with a low 5mCscore had significant immune cell infiltration and increased clinical benefit.Conclusion: This study indicated that the 5mC modification is involved in regulating TME infiltration remodeling. Targeting 5mC modification regulators might be a novel strategy to treat lung cancer.

BIOM-20. TUMOR-INTRINSIC AND PERIPHERAL FEATURES ASSOCIATE WITH SURVIVAL AFTER POLIO VIROTHERAPY IN RECURRENT GBM

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi14-vi15
Author(s):  
Michael Brown ◽  
Gao Zhang ◽  
Kevin Stevenson ◽  
Xiang Lin ◽  
Yeqing Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Inflammatory Responses ◽  
Standard Of Care ◽  
Vitro Assay ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Gene Expression Signatures ◽  
Pre Treatment ◽  
Recurrent Gbm

Abstract BACKGROUND PVSRIPO is a live-attenuated recombinant rhino:poliovirus that mediates antitumor efficacy by engaging antitumor immunity. A subset (~20%) of patients with recurrent GBM (rGBM) survive &gt;24 months after therapy. We previously reported that low tumor mutation burden (TMB) is associated with longer survival after PVSRIPO and immune checkpoint blockade therapy in rGBM, and that low TMB associates with higher inflammatory gene expression signatures in rGBM tumors. METHODS Clinical features were tested for association with survival after PVSRIPO therapy. Whole exome sequencing and RNA-sequencing of tumors were used to correlate mutational landscape, tumor mutation burden (TMB), and gene expression signatures of patient tumors with survival. An in vitro assay that measures inflammatory responses of patient PBMCs to PVSRIPO was performed. An independent cohort of paired primary and recurrent GBM tumors was used to assess longitudinal changes in TMB and gene expression signatures after standard of care treatment. RESULTS A short time to recurrence and low TMB associated with longer survival after PVSRIPO therapy; these features were not prognostic for longer survival in immunotherapy naïve rGBM cohorts. Unexpectedly, higher pre-treatment polio neutralizing antibody titers were also associated with longer survival after PVSRIPO therapy in two independent clinical cohorts. PBMCs from patients surviving longer after PVSRIPO therapy mounted higher TNF, but lower IFN-a responses after in vitro challenge with PVSRIPO. In analysis of paired primary vs recurrent GBM tumors, we discovered that patients with low TMB upon recurrence were more likely to experience increased tumor inflammation and suppression of overall TMB. Low TMB in rGBM tumors was also associated with neoantigen depletion. Collectively, these observations imply that patients with low TMB and/or shorter duration of standard of care therapy may have intact immune surveillance, and that pre-treatment immunological status may dictate survival response to polio virotherapy.

Correlation between tumor mutation burden and response to immunotherapy.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e14579-e14579 ◽  
Author(s):  
Ioana Bonta ◽  
John Florin Isac ◽  
Eyal Meiri ◽  
Dacian Bonta ◽  
Patricia Rich
Keyword(s):  
Lung Cancer ◽  
Stable Disease ◽  
Roc Analysis ◽  
Response To Therapy ◽  
Tumor Type ◽  
Protein Coding ◽  
Primary Tumors ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
The Difference

e14579 Background: The use of immunotherapy is exponentially increasing in treatment of patients with advanced solid tumors. However, the response rates vary significantly between different tumor types and even within same tumor type (e.g. in lung cancer approx. 1 in 4 patients respond to immunotherapy). In order to better identify patients that will respond to immunotherapy, several markers have been proposed. Tumor mutation burden (TMB) has emerged more recently as a quantitative marker that can help predict responses to immunotherapies across different cancers, including melanoma, lung cancer and bladder cancer. TMB is a measure of the overall number of somatic protein coding mutations occurring in the tumor specimen. Methods: We analyzed 54 consecutive patients treated with immunotherapy at our institution for which we had genomic sequencing (FoundationOne). There were 39 lung cases and 15 non-lung (GI, GU, sarcoma). For 30 cases we had TMB data. Favorable response was defined as stable disease or response to therapy at 3 months. The relationship between TMB and tumor response was explored using ROC analysis. Results: The probability of a favorable response to immunotherapy in our patient dataset was 57% (31/54 patients). Among the patients with known TMB 60% (18/30) had a favorable response (stable disease or response to therapy). The favorable response rate for tumors originating in the lung was 64% (25/39) and for non-lung primary tumors was 40% (6/15). The difference was not statistically significant, with p = 0.12. Higher TMB values were correlated with increased probability of a favorable response. ROC analysis demonstrated an Az of 74% for TMB values in differentiating between patients with and without a favorable response. A TMB cutoff value of 8 mutations/megabase yielded a sensitivity of 95% and a specificity of 58% for predicting favorable response. Conclusions: In our data base 57%of patients with different solid cancers had favorable response to immunotherapy, in second line and beyond .Higher TMB correlated with higher likelihood of response to immunotherapy, independent of the primary site of cancer.

scholarly journals 330 Integration of molecular cancer classification and next-generation sequencing to identify metastatic patients eligible for immune checkpoint inhibitors

2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A356-A356
Author(s):  
Daruka Mahadevan ◽  
Li Ma ◽  
Kai Treuner ◽  
Jenna Wong ◽  
Catherine Schnabel
Keyword(s):  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
Predictive Biomarkers ◽  
Tumor Type ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Biomarker Testing ◽  
Cancer Types ◽  
Tumor Types

BackgroundImmune checkpoint inhibitors (ICIs) have improved patient outcomes and are a new standard of care for treating a variety of cancers. Eligibility for ICIs is established through determination of tumor type and use of predictive biomarkers. PD-L1, microsatellite instability (MSI), and tumor mutation burden (TMB) are FDA-approved predictive biomarkers for ICI therapies. However, the validity of these biomarkers remains controversial, as studies have shown a failure to predict ICI response in many cancer types.1 2 The 92-gene assay (CancerTYPE ID) is a validated gene expression classifier of 50 tumor types and subtypes for metastatic patients with ambiguous diagnoses. CancerTYPE ID provides critical cancer type identification to guide ICI treatment eligibility and selection. In the current study, analyses integrating tumor type with multimodal biomarker testing for PD-L1 and TMB were evaluated to identify patients for ICI eligibility.MethodsMOSAIC (Molecular Synergy to Advance Individualized Cancer Care) is an IRB-approved, de-identified database of CancerTYPE ID results from 2572 patients with tumor-specific multimodal biomarker testing by next-generation sequencing for TMB and immunohistochemistry for PD-L1. The Cochran-Mantel-Haenszel test was used to evaluate the relationship between PD-L1 and TMB across tumor types.ResultsTumor type was determined in 2377 of 2572 cases (92.4%), comprising 27 different tumor types including 14 tumor types with FDA-approved ICI therapies. Among the top 20 tumor types, PD-L1 was present in a larger proportion of tumors (weighted mean=78.9%, range=58.3%–100%) versus TMB (20.9%, 0%–72.7%) (figure 1). Varying expression levels of PD-L1 and TMB were noted across tumor types (Figure 1), and no relationship between PD-L1 and TMB (P=0.15) was observed. Prevalence of high TMB in melanoma (42.9%) and lung adenocarcinoma (38.9%), which are more likely to respond to ICI treatment, are consistent with published data; however, prevalence of high TMB in mesothelioma (20.0%), sarcoma (23.6%) and prostatic adenocarcinoma (33.3%), which are not likely to respond to ICI treatment, are higher than previously reported.3Abstract 330 Figure 1Prevalence of PD-L1 expression and high TMB in the 27 identified tumor typesConclusionsTumor type classification and cellular context are critical for ICI eligibility. CancerTYPE ID successfully differentiated 14 ICI-eligible tumor types from 13 non-ICI-eligible tumor types. Further, since there is no relationship between PD-L1 and TMB for different tumor types, accurate tumor type identification is necessary to select the most appropriate biomarker. This highlights the clinical utility of CancerTYPE ID combined with multimodal biomarker testing to guide ICI treatment and predict response based on tumor type identification, which may improve outcomes in patients with metastatic cancer.ReferencesMcGrail DJ, Pilié PG, Rashid NU, et al. High tumor mutation burden fails to predict immune checkpoint blockade response across all cancer types. Ann Oncol 2021;32(5):661–672.Gjoerup O, Brown CA, Ross JS, et al. Identification and utilization of biomarkers to predict response to immune checkpoint inhibitors. AAPS J 2020;22(6):132.Yarchoan M, Albacker LA, Hopkins AC, et al. PD-L1 expression and tumor mutational burden are independent biomarkers in most cancers. JCI Insight 2019;4(6):e126908.

scholarly journals Characterization of m6A RNA Methylation Regulators Predicts Survival and Immunotherapy in Lung Adenocarcinoma

2021 ◽  
Vol 12 ◽  
Author(s):  
Minggao Zhu ◽  
Yachao Cui ◽  
Qi Mo ◽  
Junwei Zhang ◽  
Ting Zhao ◽  
...  
Keyword(s):  
Tumor Microenvironment ◽  
Lung Adenocarcinoma ◽  
Immune Cell ◽  
Clinical Success ◽  
Cell Infiltration ◽  
Immune Cell Infiltration ◽  
Consensus Clustering ◽  
Tumor Mutation Burden ◽  
Mutation Burden ◽  
Score Model

N6-methyladenosine (m6A) RNA modification is a reversible mechanism that regulates eukaryotic gene expression. Growing evidence has demonstrated an association between m6A modification and tumorigenesis and response to immunotherapy. However, the overall influence of m6A regulators on the tumor microenvironment and their effect on the response to immunotherapy in lung adenocarcinoma remains to be explored. Here, we comprehensively analyzed the m6A modification patterns of 936 lung adenocarcinoma samples based on 24 m6A regulators. First, we described the features of genetic variation in these m6A regulators. Many m6A regulators were aberrantly expressed in tumors and negatively correlated with most tumor-infiltrating immune cell types. Furthermore, we identified three m6A modification patterns using a consensus clustering method. m6A cluster B was preferentially associated with a favorable prognosis and enriched in metabolism-associated pathways. In contrast, m6A cluster A was associated with the worst prognosis and was enriched in the process of DNA repair. m6A cluster C was characterized by activation of the immune system and a higher stromal cell score. Surprisingly, patients who received radiotherapy had a better prognosis than patients without radiotherapy only in the m6A cluster C group. Subsequently, we constructed an m6A score model that qualified the m6A modification level of individual samples by using principal component analysis algorithms. Patients with high m6A score were characterized by enhanced immune cell infiltration and prolonged survival time and were associated with lower tumor mutation burden and PD-1/CTLA4 expression. The combination of the m6A score and tumor mutation burden could accurately predict the prognosis of patients with lung adenocarcinoma. Furthermore, patients with high m6A score exhibited greater prognostic benefits from radiotherapy and immunotherapy. This study demonstrates that m6A modification is significantly associated with tumor microenvironment diversity and prognosis. A comprehensive evaluation of m6A modification patterns in single tumors will expand our understanding of the tumor immune landscape. In addition, our m6A score model demonstrated that the level of immune cell infiltration plays a significant role in cancer immunotherapy and provides a basis to increase the efficiency of current immune therapies and promote the clinical success of immunotherapy.

scholarly journals m6A Regulators Mediated Methylation Modification Patterns and Tumor Microenvironment Infiltration Characterization In Nasopharyngeal Carcinoma

2022 ◽  
Vol 12 ◽  
Author(s):  
Zijian Liu ◽  
Jinlan He ◽  
Jiaqi Han ◽  
Jiangping Yang ◽  
Wenjun Liao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Nasopharyngeal Carcinoma ◽  
Tumor Microenvironment ◽  
Lower Risk ◽  
Biological Function ◽  
Tumor Characteristics ◽  
Tumor Mutation Burden ◽  
Therapeutic Advantage ◽  
Mutation Burden

BackgroundThe role of RNA N6-methyladenosine (m6A) modification in tumor progression and metastasis has been demonstrated. Nonetheless, potential biological function of m6A modification patterns in nasopharyngeal carcinoma (NPC) remains unknown.MethodsThe m6A modification patterns were comprehensively evaluated based on 26 m6A regulators in NPC, and m6A subtype and also m6A score were identified and systematically correlated with representative tumor characteristics.ResultsTwo distinct m6A subtypes were determined and were highly consistent with immune activated and immune suppressed phenotypes, respectively. More representative m6A scores of individual tumors could predict tumor microenvironment (TME) infiltration, mRNA based stemness index (mRNAsi), EBV gene expression, genetic variation, and prognosis of NPC patients. Low m6A score, characterized by activation of immunity and suppression of mRNAsi and EBV gene, indicated an activated TME phenotype and better PFS and also lower risk of recurrence and metastasis. High m6A score, characterized by activation of Wnt and NF-κB signaling pathway and lack of effective immune infiltration, indicated an immune suppressed TME phenotype and poorer survival. Low m6A score was also correlated with increased tumor mutation burden (TMB) and better response to immunotherapy, and vice versa. A significant therapeutic advantage in patients with low m6A score was confirmed with an anti-PDL1 immunotherapy cohort.Conclusionsm6A patterns played an important role in the diversity and complexity of TME. m6A score could be used to evaluate the m6A pattern of individual tumor to enhance our understanding of TME infiltration and guide more effective immunotherapy strategies.

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