scholarly journals BRAF Mutation as a Potential Therapeutic Target for Checkpoint Inhibitors: A Comprehensive Analysis of Immune Microenvironment in BRAF Mutated Colon Cancer

Author(s):  
Shuyi Cen ◽  
Kun Liu ◽  
Yu Zheng ◽  
Jianzhen Shan ◽  
Chao Jing ◽  
...  

BRAF mutated colon cancer presents with poor survival, and the treatment strategies are controversial. The tumor microenvironment, which plays a key role in tumorigenesis as well as responses to treatments, of this subtype is largely unknown. In the present study, we analyzed the differences of immune microenvironments between BRAF mutated and BRAF wild-type colon cancer utilizing datasets from The Cancer Genome Atlas and Gene Expression Omnibus and confirmed the findings by tissue specimens of patients. We found that BRAF mutated colon cancer had more stromal cells, more immune cell infiltration, and lower tumor purity. Many immunotherapeutic targets, including PD-1, PD-L1, CTLA-4, LAG-3, and TIM-3, were highly expressed in BRAF mutated patients. BRAF mutation was also correlated with higher proportions of neutrophils and macrophages M1, and lower proportions of plasma cells, dendritic cells resting, and T cells CD4 naïve. In conclusion, our study demonstrates a different pattern of the immune microenvironment in BRAF mutated colon cancer and provides insights into the future use of checkpoint inhibitors in this subgroup of patients.

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Yixin Xu ◽  
Junjie Hu ◽  
Can Cao ◽  
Mili Zhang ◽  
Youdong Liu ◽  
...  

Despite dramatic responses to immune checkpoint inhibitors (ICIs) in patients with colon cancer (CC) harboring deficient mismatch repair (dMMR), more than half of these patients ultimately progress and experience primary or secondary drug resistance. There is no useful biomarker that is currently validated to accurately predict this resistance or stratify patients who may benefit from ICI-based immunotherapy. As hypoxic and acidic tumor microenvironment would greatly impair tumor-suppressing functions of tumor-infiltrating lymphocytes (TILs), we sought to explore distinct immunological phenotypes by analysis of the intratumoral hypoxia state using a well-established gene signature. Based on the Gene Expression Omnibus (GEO) (n = 88) and The Cancer Genome Atlas (TCGA) (n = 49) databases of patients with CC, we found that dMMR CC patients could be separated into normoxia subgroup (NS) and hypoxia subgroup (HS) with different levels of expression of hypoxia-related genes (lower in NS group and higher in HS group) using NMF package. Tumoral parenchyma in the HS group had a relatively lower level of immune cell infiltration, particularly CD8+ T cells and M1 macrophages than the NS group, and coincided with higher expression of immune checkpoint molecules and C-X-C motif chemokines, which might be associated with ICI resistance and prognosis. Furthermore, three genes, namely, MT1E, MT2A, and MAFF, were identified to be differentially expressed between NS and HS groups in both GEO and TCGA cohorts. Based on these genes, a prognostic model with stable and valuable predicting ability has been built for clinical application. In conclusion, the varying tumor-immune microenvironment (TIME) classified by hypoxia-related genes might be closely associated with different therapeutic responses of ICIs and prognosis of dMMR CC patients.


2020 ◽  
Author(s):  
Yingying Cao ◽  
Youwei Zhang ◽  
Nanlin Jiao ◽  
Tiantian Sun ◽  
Yanru Ma ◽  
...  

Abstract Background: CXCL11 has been considered to be responsible for tumor development, but the specific effect of CXCL11 in colon cancer was still obscure. Therefore, the prognostic value and immunological regulation effect of CXCL11 in colon cancer were evaluated in this study.Methods: Three independent datasets were used for mRNA-related analysis: one dataset from the Cancer Genome Atlas (TCGA, n=451) and two single-cell RNA sequencing (scRNA-seq) datasets from Gene Expression Omnibus (GEO): GSE146771 and GSE132465. In addition, the patient cohort (the Yijishan Hospital cohort, YJSHC, n=108) was utilized for cell infiltration-related analysis, accordingly. Both CXCL11 mRNA expression and CXCL11+ (CXCL11-producing) cells were assessed in colon cancer, whose effect on prognosis and immunological regulation was also studied. Results: High CXCL11 expression were associated with better prognosis in colon cancer, which was still significant even if clinicopathological factors were adjusted. Furthermore, CXCL11 positively correlated with anti-tumor cells infiltration, such as CD8+ T cells and natural killer cells. Meanwhile, CXCL11 correlated positively with several genes associated with DC, NK and T recruitment,and a gene set of cytotoxic genes. Notably, CXCL11 correlated positively with several immune checkpoint related genes including of PD-L1. Conclusions: CXCL11 contributed to anti-tumor immune microenvironment and could improve prognosis in patients with colon cancer. Especially, it’s a potential approach that inducible expression of CXCL11 by genetic and pharmacological interventions is able to improve prognosis and response to anti-PD-1 (programmed cell death protein-1) antibody treatment in colon cancer. However, it requires to be verified by further prospective investigations.


2021 ◽  
Vol 12 ◽  
Author(s):  
Boyang Xu ◽  
Ziqi Peng ◽  
Guanyu Yan ◽  
Ningning Wang ◽  
Moye Chen ◽  
...  

BackgroundColon cancer is a malignant tumor with high morbidity and mortality. Researchers have tried to interpret it from different perspectives and divided it into different subtypes to facilitate individualized treatment. With the rise in the use of immunotherapy, its value in the field of tumor has begun to emerge. From the perspective of immune infiltration, this study classified colon cancer according to the infiltration of M2 macrophages in patients with colon cancer and further explored the same.MethodsCibersort algorithm was used to analyze the level of immune cell infiltration in patients with colon cancer in The Cancer Genome Atlas (TCGA) database. Weighted gene co-expression network analysis (WGCNA), Consensus Clustering analysis, Lasso analysis, and univariate Kaplan–Meier analysis were used to screen and verify the hub genes associated with M2 macrophages. Principal component analysis (PCA) was used to establish the M2 macrophage-related score (M2I Score). The correlation between M2I Score and somatic cell variation and microsatellite instability (MSI) were analyzed. Furthermore, the correlation between M2 macrophage score and differences in immunotherapy sensitivity was also explored.ResultsM2 macrophage infiltration was associated with poor prognosis. Four hub genes (ANKS4B, CTSD, TIMP1, and ZNF703) were identified as the progression-related genes associated with M2 macrophages. A stable and accurate M2I Score for M2 macrophages used in colon adenocarcinoma was determined based on four hub genes. The M2I Score was positively correlated with the tumor mutation load (TMB). The M2I Score of the group with high instability of microsatellites was higher than that of the group with low instability of microsatellites and microsatellite-stable group. Combined with the Cancer Immunome Atlas database, we concluded that patients with high M2I Scores were more sensitive to programmed cell death protein 1 (PD-1) inhibitors and PD-1 inhibitors combined with cytotoxic T-lymphocyte–associated antigen 4 (CTLA-4) inhibitors. The low-rating group may have better efficacy without immune checkpoint inhibitors or with CTLA4 inhibitors alone.ConclusionFour prognostic hub genes associated with M2 macrophages were screened to establish the M2I Score. Patients were divided into two subgroups: high M2I Score group and low M2I Score group. TMB, MSI, and sensitivity to immunotherapy were higher in the high-rated group. PD-1 inhibitors or PD-1 combined with CTLA-4 inhibitors are preferred for patients in the high-rated group who are more sensitive to immunotherapy.


2021 ◽  
Author(s):  
Meghana Pagadala ◽  
Victoria H. Wu ◽  
Eva Perez-Guijarro ◽  
Hyo Kim ◽  
Andrea Castro ◽  
...  

With the continued promise of immunotherapy as an avenue for treating cancer, understanding how host genetics contributes to the tumor immune microenvironment (TIME) is essential to tailoring cancer risk screening and treatment strategies. Using genotypes from over 8,000 European individuals in The Cancer Genome Atlas (TCGA) and 137 heritable tumor immune phenotype components (IP components), we identified and investigated 482 TIME associations and 475 unique TIME-associated variants. Many TIME-associated variants influence gene activities in specific immune cell subsets, such as macrophages and dendritic cells, and interact to promote more extreme TIME phenotypes. TIME-associated variants were predictive of immunotherapy response in human cohorts treated with immune-checkpoint blockade (ICB) in 3 cancer types, causally implicating specific immune-related genes that modulate myeloid cells of the TIME. Moreover, we validated the function of these genes in driving tumor response to ICB in preclinical studies. Through an integrative approach, we link host genetics to TIME characteristics, informing novel biomarkers for cancer risk and target identification in immunotherapy.


Author(s):  
Jun-Nan Guo ◽  
Du Chen ◽  
Shen-Hui Deng ◽  
Jia-Rong Huang ◽  
Jin-Xuan Song ◽  
...  

Abstract Background The left-sided and right-sided colon cancer (LCCs and RCCs, respectively) have unique molecular features and clinical heterogeneity. This study aimed to identify the characteristics of immune cell infiltration (ICI) subtypes for evaluating prognosis and therapeutic benefits. Methods The independent gene datasets, corresponding somatic mutation and clinical information were collected from The Cancer Genome Atlas and Gene Expression Omnibus. The ICI contents were evaluated by “ESTIMATE” and “CIBERSORT.” We performed two computational algorithms to identify the ICI landscape related to prognosis and found the unique infiltration characteristics. Next, principal component analysis was conducted to construct ICI score based on three ICI patterns. We analyzed the correlation between ICI score and tumor mutation burden (TMB), and stratified patients into prognostic-related high- and low- ICI score groups (HSG and LSG, respectively). The role of ICI scores in the prediction of therapeutic benefits was investigated by "pRRophetic" and verified by Immunophenoscores (IPS) (TCIA database) and an independent immunotherapy cohort (IMvigor210). The key genes were preliminary screened by weighted gene co-expression network analysis based on ICI scores. And they were further identified at various levels, including single cell, protein and immunotherapy response. The predictive ability of ICI score for prognosis was also verified in IMvigor210 cohort. Results The ICI features with a better prognosis were marked by high plasma cells, dendritic cells and mast cells, low memory CD4+ T cells, M0 macrophages, M1 macrophages, as well as M2 macrophages. A high ICI score was characterized by an increased TMB and genomic instability related signaling pathways. The prognosis, sensitivities of targeted inhibitors and immunotherapy, IPS and expression of immune checkpoints were significantly different in HSG and LSG. The genes identified by ICI scores and various levels included CA2 and TSPAN1. Conclusion The identification of ICI subtypes and ICI scores will help gain insights into the heterogeneity in LCC and RCC, and identify patients probably benefiting from treatments. ICI scores and the key genes could serve as an effective biomarker to predict prognosis and the sensitivity of immunotherapy.


BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Chao Yang ◽  
Shuoyang Huang ◽  
Fengyu Cao ◽  
Yongbin Zheng

Abstract Background and aim Lipid metabolic reprogramming is considered to be a new hallmark of malignant tumors. The purpose of this study was to explore the expression profiles of lipid metabolism-related genes (LMRG) in colorectal cancer (CRC). Methods The lipid metabolism statuses of 500 CRC patients from the Cancer Genome Atlas (TCGA) and 523 from the Gene Expression Omnibus (GEO GSE39582) database were analyzed. The risk signature was constructed by univariate Cox regression and least absolute shrinkage and selection operator (LASSO) Cox regression. Results A novel four-LMRG signature (PROCA1, CCKBR, CPT2, and FDFT1) was constructed to predict clinical outcomes in CRC patients. The risk signature was shown to be an independent prognostic factor for CRC and was associated with tumour malignancy. Principal components analysis demonstrated that the risk signature could distinguish between low- and high-risk patients. There were significantly differences in abundances of tumor-infiltrating immune cells and mutational landscape between the two risk groups. Patients in the low-risk group were more likely to have higher tumor mutational burden, stem cell characteristics, and higher PD-L1 expression levels. Furthermore, a genomic-clinicopathologic nomogram was established and shown to be a more effective risk stratification tool than any clinical parameter alone. Conclusions This study demonstrated the prognostic value of LMRG and showed that they may be partially involved in the suppressive immune microenvironment formation.


2021 ◽  
Author(s):  
Pingfan Wu ◽  
Xiaowen Zhao ◽  
Ling Xue ◽  
Xiaojing Yang ◽  
Yuxiang Shi ◽  
...  

Abstract Considerable evidence suggests that N6-methyladenosine (m6A) is involved in the regulation of long non-coding RNA (lncRNA), whichparticipates in the occurrence, development and prognosis of tumorscancerBut the relationship between m6A regulators-related lncRNA (mRlncRNA) and lung adenocarcinoma (LUAD) remains unclear. This study aims to determine a feature based on mRlncRNA for prognostic evaluation of LUAD patients. By integrating the gene expression data of LUAD and normal samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) database, the m6A gene and mRlncRNA with imbalanced expression were screened out. Then we used the least absolute shrinkage and selection operator (LASSO) to obtain the 13-lncRNA prognostic signature in the TCGA training cohort. Patients were divided into two risk groups based on the risk score of lncRNAs characteristics, and their overall survival (OS) was significantly different. The predictive power of this signature was verified in TCGA testing cohort and entire TCGA cohort. These landmark lncRNAs were involved in several biologiocal processes and pathways related to cell cycle, DNA replication, P53 signaling pathway and mismatch repair. Besides, the high-risk group was low-response to cisplatin, while high-response to mitomycin, docetaxel and immunotherapy. In conclusion, we identified a 13-mRlncRNA model associated with prognosis and treatment sensitivity in LUAD, which may provide clues about the influence of m6A on lncRNA in LUAD and promote the further improvement of LUAD individualized treatment strategies.


2022 ◽  
Vol 12 ◽  
Author(s):  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.


2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A270-A270
Author(s):  
Chen Zhao ◽  
Abigail Wong-Rolle ◽  
Prajan Divakar ◽  
Katherine Calvo ◽  
Christopher Hourigan

BackgroundRelapsed or refractory Acute Myeloid Leukemia (R-AML) is a deadly disease with an inadequate response rate to current treatments. Recent advances in immunotherapy shed light on R-AML, and several clinical trials have shown promising potential for combining immune checkpoint inhibitors (ICIs) with hypomethylating agents. A deeper understanding of the tumor-immune microenvironment in R-AML during combination ICI treatment is urgently needed for developing better therapeutics and stratifying treatment strategies.MethodsTo dissect the tumor-immune interactions in the bone marrow microenvironment, we employed nanoString GeoMx Digital Spatial Profiler (DSP) and performed a spatial-transcriptomic analysis of patients with R-AML who received pembrolizumab and decitabine. We compared the transcriptomic profiles and TCR clonalities of tumor-interacting T cells, bystander T cells, and other cells at baseline, post-pembrolizumab treatment, and post-decitabine, which enable us to identify R-AML’s suppressive immune microenvironment and immune cells’ responses to ICI and hypomethylating agent.ResultsWe obtained the spatial-transcriptomic profiles of T cells, stromal cells, and leukemia cells in patients with R-AML at different treatment points. Our TCR-specific probes were able to track T cell clonal changes during treatments.ConclusionsR-AML harbored a complex tumor immune microenvironment and diverse T cell clonality.AcknowledgementsThis research was supported in part by the Intramural Research Program of the NCI (the Center for Cancer Research), NHLBI, and NIH Clinical Center.Ethics ApprovalThis study is approved by NHLBI IRB.


2021 ◽  
Vol 9 (Suppl 3) ◽  
pp. A954-A955
Author(s):  
Jacob Kaufman ◽  
Doug Cress ◽  
Theresa Boyle ◽  
David Carbone ◽  
Neal Ready ◽  
...  

BackgroundLKB1 (STK11) is a commonly disrupted tumor suppressor in NSCLC. Its loss promotes an immune exclusion phenotype with evidence of low expression of interferon stimulated genes (ISG) and decreased microenvironment immune infiltration.1 2 Clinically, LKB1 loss induces primary immunotherapy resistance.3 LKB1 is a master regulator of a complex downstream kinase network and has pleiotropic effects on cell biology. Understanding the heterogeneous phenotypes associated with LKB1 loss and their influence on tumor-immune biology will help define and overcome mechanisms of immunotherapy resistance within this subset of lung cancer.MethodsWe applied multi-omic analyses across multiple lung adenocarcinoma datasets2 4–6 (>1000 tumors) to define transcriptional and genetic features enriched in LKB1-deficient lung cancer. Top scoring phenotypes exhibited heterogeneity across LKB1-loss tumors, and were further interrogated to determine association with increased or decreased markers of immune activity. Further, immune cell-types were estimated by Cibersort to identify effects of LKB1 loss on the immune microenvironment. Key conclusions were confirmed by blinded pathology review.ResultsWe show that LKB1 loss significantly affects differentiation patterns, with enrichment of ASCL1-expressing tumors with putative neuroendocrine differentiation. LKB1-deficient neuroendocrine tumors had lower expression of Interferon Stimulated Genes (ISG), MHC1 and MHC2 components, and immune infiltration compared to LKB1-WT and non-neuroendocrine LKB1-deficient tumors (figure 1).The abundances of 22 immune cell types assessed by Cibersort were compared between LKB1-deficient and LKB1-WT tumors. We observe skewing of immune microenvironmental composition by LKB1 loss, with lower abundance of dendritic cells, monocytes, and macrophages, and increased levels of neutrophils and plasma cells (table 1). These trends were most pronounced among tumors with neuroendocrine differentiation, and were concordant across three independent datasets. In a confirmatory subset of 20 tumors, plasma cell abundance was assessed by a blinded pathologist. Pathologist assessment was 100% concordant with Cibersort prediction, and association with LKB1 loss was confirmed (P=0.001).Abstract 909 Figure 1Immune-associated Gene Expression Profiles Affected by Neuroendocrine Differentiation within LKB1-Deficient Lung Adenocarcinomas. Gene expression profiles corresponding to five immune-associated phenotypes are shown with bars indicating average GEP scores for tumors grouped according to LKB1 and neuroendocrine status as indicated. P-values represent results from Student’s T-test between groups as indicated.Abstract 909 Table 1LKB1 Loss Affects Composition of Immune Microenvironment. Values indicate log10 P-values comparing LKB1-loss to LKB1-WT tumors. Positive (red) indicates increased abundance in LKB1 loss. Negative (blue) indicates decreased abundance.ConclusionsWe conclude that tumor differentiation patterns strongly influence the immune microenvironment and immune exclusion characteristics of LKB1-deficient tumors. Neuroendocrine differentiation is associated with the strongest immune exclusion characteristics and should be evaluated clinically for evidence of immunotherapy resistance. A novel observation of increased plasma cell abundance is observed across multiple datasets and confirmed by pathology. Causal mechanisms linking differentiation status to immune activity is not well understood, and the functional role of plasma cells in the immune biology of LKB1-deficient tumors is undefined. These questions warrant further study to inform precision immuno-oncology treatments for these patients.AcknowledgementsThis work was funded by SITC AZ Immunotherapy in Lung Cancer grant (SPS256666) and DOD Lung Cancer Research Program Concept Award (LC180633).ReferencesSkoulidis F, Byers LA, Diao L, et al. Co-occurring genomic alterations define major subsets of KRAS-mutant lung adenocarcinoma with distinct biology, immune profiles, and therapeutic vulnerabilities. Cancer Discov 2015;5:860–77.Schabath MB, Welsh EA, Fulp WJ, et al. Differential association of STK11 and TP53 with KRAS mutation-associated gene expression, proliferation and immune surveillance in lung adenocarcinoma. Oncogene 2016;35:3209–16.Skoulidis F, Goldberg ME, Greenawalt DM, et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discovery 2018;8:822-835.Cancer Genome Atlas Research Network. Comprehensive molecular profiling of lung adenocarcinoma. Nature 2014;511:543–50.Chitale D, Gong Y, Taylor BS, et al. An integrated genomic analysis of lung cancer reveals loss of DUSP4 in EGFR-mutant tumors. Oncogene 2009;28:2773–83.Shedden K, Taylor JM, Enkemann SA, et al. Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study. Nat Med 2008;14:822–7.


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