Dataset Information

Transcriptional Profiles from Paired Normal Samples Offer Complementary Information on Cancer Patient Survival--Evidence from TCGA Pan-Cancer Data.

ABSTRACT: Although normal tissue samples adjacent to tumors are sometimes collected from patients in cancer studies, they are often used as normal controls to identify genes differentially expressed between tumor and normal samples. However, it is in general more difficult to obtain and clearly define paired normal samples, and whether these samples should be treated as "normal" due to their close proximity to tumors. In this article, by analyzing the accrued data in The Cancer Genome Atlas (TCGA), we show the surprising results that the paired normal samples are in general more informative on patient survival than tumors. Different lines of evidence suggest that this is likely due to tumor micro-environment instead of tumor cell contamination or field cancerization effect. Pathway analyses suggest that tumor micro-environment may play an important role in cancer patient survival either by boosting the adjacent metabolism or the in situ immunization. Our results suggest the potential benefit of collecting and profiling matched normal tissues to gain more insights on disease etiology and patient progression.

SUBMITTER: Huang X

PROVIDER: S-EPMC4738355 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Transcriptional Profiles from Paired Normal Samples Offer Complementary Information on Cancer Patient Survival--Evidence from TCGA Pan-Cancer Data.

Huang Xiu X Stern David F DF Zhao Hongyu H

Scientific reports 20160203

Although normal tissue samples adjacent to tumors are sometimes collected from patients in cancer studies, they are often used as normal controls to identify genes differentially expressed between tumor and normal samples. However, it is in general more difficult to obtain and clearly define paired normal samples, and whether these samples should be treated as "normal" due to their close proximity to tumors. In this article, by analyzing the accrued data in The Cancer Genome Atlas (TCGA), we sho ...[more]

PMID: 26837275

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Project description:Despite progress in understanding the biology of adrenocortical carcinoma (ACC), treatment options have not dramatically changed in the last three decades, nor have we learned how to avoid some of its long-term side effects. Our goal was to improve the understanding of immune pathways that may include druggable targets to enhance immune responses of patients with ACC, focusing on immune evasion and the activation of immune cells against ACC. Our strategy was aimed at improving insight regarding gene expression without steroid interference. Using approaches based on high and low steroid phenotypes (HSP and LSP, respectively), we characterized immune pathways using The Cancer Genome Atlas (TCGA) ACC cohort data. Although previous studies have suggested that patients with ACC receive minimal benefit from immunotherapy, high expression of immune modulators was noted in patients with LSP, suggesting the activation of these biomarkers may be an important adjuvant therapy target after clearance of excess glucocorticoids. In addition, patients with LSP ACC had higher immune cell infiltration than patients with HSP ACC and other cancer subtypes. Our findings can be summarized as follows (1): we confirmed and improved the definition of two immune response pathways to ACC (HSP and LSP) based on in silico transcriptome analysis (2), we demonstrated the steroid profile should be considered, otherwise analyses of ACC immune characteristics can generate confounding results (3), among the overexpressed immunotherapy targets, we demonstrated that LSP was rich in PDCD1LG2 (PD-L2) and both HSP and LSP overexpressed CD276 (B7-H3), which was associated with resistance to anti-PD1 therapy and may have accounted for the modest results of previous clinical trials, and (4) identification of patients with LSP or HSP ACC can be used to help determine whether immunotherapy should be used. In conclusion, we highlighted the differences between LSP and HSP, drawing attention to potential therapeutic targets (CD276, PDCD1, and PDCD1LG2). Treatments to reduce immune evasion, as well as the use of other natural and pharmacological immune activators, should include prior pharmacological inhibition of steroidogenesis. Attempts to combine these with tumor cell proliferation inhibitors, if they do not affect cells of the immune system, may produce interesting results.

Dataset Information

Transcriptional Profiles from Paired Normal Samples Offer Complementary Information on Cancer Patient Survival--Evidence from TCGA Pan-Cancer Data.

Publications

Transcriptional Profiles from Paired Normal Samples Offer Complementary Information on Cancer Patient Survival--Evidence from TCGA Pan-Cancer Data.

Similar Datasets

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