Mutational Analysis of Patients With Colorectal Cancer in CALGB/SWOG 80405 Identifies New Roles of Microsatellite Instability and Tumor Mutational Burden for Patient Outcome

Innocenti, Federico; Ou, Fang Shu; Qu, Xueping; Zemla, Tyler; Niedzwiecki, Donna; Tam, Rachel; Mahajan, Shilpi; Goldberg, Richard M.; Bertagnolli, Monica M.; Blanke, Charles D.; Sanoff, Hanna K.; Atkins, James N.; Polite, Blasé N.; Venook, Alan P.; Lenz, Heinz Josef; Kabbarah, Omar

doi:10.1200/jco.18.01798

Cited by 253 publications

(221 citation statements)

References 16 publications

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“…A high TMB probably reflects the presence of mutation-associated neoantigens, with consequent increased lymphocyte infiltration in the tumor microenvironment. This phenomenon has been observed in other tumors [26,27]. The tumor microenvironment consists of immune cells, mesenchymal cells, endothelial cells, extracellular matrix (ECM) molecules, and inflammatory mediators.…”

Section: Discussionmentioning

confidence: 61%

Identification of gene expression profiles and immune cell infiltration signatures between low and high tumor mutation burden groups in bladder cancer

Wang

Liu

et al. 2020

Int. J. Med. Sci.

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Bladder cancer is one of the most commonly diagnosed tumors and is results from the accumulation of somatic mutations in the DNA. Tumor mutation burden (TMB) has been associated with cancer immunotherapeutic response. In this study, we attempted to explore the correlation between TMB and cancer prognosis. Identify the different expressed genes and immune cell infiltration signatures between low and high TMB group. Mutation data, gene expression profiles and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. Patients were divided into high and low TMB groups, allowing differentially expressed genes (DEGs) to be identified. Functional enrichment and protein-protein interaction (PPI) network analysis were used to identify the functions of the DEGs. And immune cell infiltration signatures were evaluated by CIBERSORT algorithm. These results shown that high TMB was significantly associated with prognosis. We obtained a list of TMB related genes which may influence the infiltrations of immune cells. We also found a higher proportion of CD8 T cells, CD4 T cells and NK cells in the high TMB group. Our data suggest that higher TMB tends to promote the infiltrations of T cells and NK cells and patients with higher TMB may achieve a more favorable prognosis in bladder cancer.

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Section: Discussionmentioning

confidence: 61%

Identification of gene expression profiles and immune cell infiltration signatures between low and high tumor mutation burden groups in bladder cancer

Wang

Liu

et al. 2020

Int. J. Med. Sci.

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“…In comparison with other groups cluster 2 have more mutated gene and a higher TMB. It has been observed in other tumors that high TMB may reflects the presence of new antigens, thereby increasing lymphocyte infiltration in the tumor microenvironment [30,31]. The cluster 3 had similar mutation characteristics with cluster 1; TP53 and TTN were the major mutant genes.…”

Section: Discussionmentioning

confidence: 77%

Profiles of Immune Infiltration in Bladder Cancer and its Clinical Significance: an Integrative Genomic Analysis

Zhu

Liu

et al. 2020

Int. J. Med. Sci.

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Tumor-infiltrating immune cells are closely related to the prognosis of bladder cancer. Analysis of tumor infiltrating immune cells is usually based on immunohistochemical analysis. Since many immune cell marker proteins are not specific for different immune cells, which may induce misleading or incomplete. CIBERSORT is an algorithm to estimate specific cell types in a mixed cell population using gene expression data. In this study, the CIBERSORT algorithm was used to identify the immune cell infiltration signatures. The gene expression profiles, mutation data, and clinical data were collected from The Cancer Genome Atlas (TCGA) database. Unsupervised consensus clustering was used to acquire the immune cell infiltration subtypes of bladder cancer based on the fractions of 22 immune cell types. Four immune cell clusters with different immune infiltrate and mutation characteristics were identified. In addition, this stratification has a prognostic relevance, with cluster 2 having the best outcome, cluster 1 the worst. These clusters showed distinct mRNA expression patterns. The characteristic genes in subtype cluster 1 were mainly involved in cell division, those in subtype cluster 2 were mainly related in antigen processing and presentation, those in subtype cluster 3 were mainly involved in epidermal cell differentiation, and those in subtype cluster 4 were mainly related in the humoral immune response. These differences may affect the development of the bladder cancer, the sensitivity to treatment as well as the prognosis. Through further validation, this study may contribute to the development of personalized therapy and precision medical treatments.

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“…www.nature.com/scientificreports www.nature.com/scientificreports/ Several studies demonstrated that hypermutation is associated with increased TILs in TME due to neoantigens generation 5,7,13 . Innocenti and colleagues recently reported that higher tumor mutation rates correlated with better survival in patients with microsatellite stable (MSS) colorectal cancer, where mutation rates are far less common than MSI-high tumor 51 . They suggested that the survival benefit was a reflection of increased neoantigens Figure 6.…”

Section: Discussionmentioning

confidence: 99%

Biologically Aggressive Phenotype and Anti-cancer Immunity Counterbalance in Breast Cancer with High Mutation Rate

Takahashi

Asaoka

Yan

et al. 2020

Sci Rep

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While cancer cells gain aggressiveness by mutations, abundant mutations release neoantigens, attracting anti-cancer immune cells. We hypothesized that in breast cancer (BC), where mutation is less common, tumors with high mutation rates demonstrate aggressive phenotypes and attract immune cells simultaneously. High mutation rates were defined as the top 10% of the mutation rate, utilizing TCGA and METABRIC transcriptomic data. Mutation rate did not impact survival although high mutation BCs were associated with aggressive clinical features, such as more frequent in ER-negative tumors (p < 0.01), in triple-negative subtype (p = 0.03), and increased MKI-67 mRnA expression (p < 0.01) in both cohorts. Tumors with high mutation rates were associated with APOBEC3B and homologous recombination deficiency, increasing neoantigen loads (all p < 0.01). Cell proliferation and immune activity pathways were enriched in BCs with high mutation rates. Furthermore, there were higher lymphocytes and M1 macrophage infiltration in high mutation BCs. Additionally, T-cell receptor diversity, cytolytic activity score (CYT), and T-cell exhaustion marker expression were significantly elevated in BCs with high mutation rates (all p < 0.01), indicating strong immunogenicity. In conclusion, enhanced immunity due to neoantigens can be one of possible forces to counterbalance aggressiveness of a high mutation rate, resulting in similar survival rates to low mutation BCs. Accumulation of somatic mutations, or somatic genome instability, has been the principle of carcinogenesis; cancer cells stem from a clone that has gained the somatically acquired genetic abnormalities, leading to malignant transformation and further progression 1. With advances in next-generation sequencing technologies, clinical interest in assessing mutation burden and identifying specific mutations in certain cancer types has been growing to utilize targeted therapies or to assess tumor biology, such as FoundationOne genomic panel testing 2-4. Mutation rates are variable among cancer types and outliers with significantly high mutation burdens, hypermutation, do exist in many cancer types 5. Interestingly, the definition of hypermutation has been variable in the literature 5-7 , although the common definition is usually greater than 10-100 mutations per Mega base pairs (Mbps). Campbell and colleagues recently performed comprehensive analysis of hypermutation in various tumor types, providing more insight into tumor evolution and identifying possible clinically actionable mutation signatures 6. The etiology of hypermutation varies between cancer types; ultraviolet (UV) light is the significant cause of mutations in melanoma, while smoking causes the mutations in non-small cell lung cancer (NSCLC) and head and neck squamous cell carcinoma (SCC) 7,8. Whereas UV light and smoking are examples of exogenous mutagens, there are endogenous processes for mutation, such as microsatellite instability (MSI), and Apolipoprotein

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Mutational Analysis of Patients With Colorectal Cancer in CALGB/SWOG 80405 Identifies New Roles of Microsatellite Instability and Tumor Mutational Burden for Patient Outcome

Cited by 253 publications

References 16 publications

Identification of gene expression profiles and immune cell infiltration signatures between low and high tumor mutation burden groups in bladder cancer

Identification of gene expression profiles and immune cell infiltration signatures between low and high tumor mutation burden groups in bladder cancer

Profiles of Immune Infiltration in Bladder Cancer and its Clinical Significance: an Integrative Genomic Analysis

Biologically Aggressive Phenotype and Anti-cancer Immunity Counterbalance in Breast Cancer with High Mutation Rate

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