An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles

Li, Mengyuan; Zhang, Zhilan; Li, Lin; Wang, Xiaosheng

doi:10.1038/s42003-020-01230-7

Cited by 64 publications

(82 citation statements)

References 67 publications

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“…GI is a major cause of tumor heterogeneity within and between tumors (5). Moreover, it is broadly recognized that GI is closely related with the progression and prognosis of tumors (6)(7)(8)(9).…”

Section: Introductionmentioning

confidence: 99%

Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

Yang

Xiong

2021

Front. Oncol.

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BackgroundClear cell renal cell carcinoma (ccRCC) is a kind of frequently diagnosed cancer, leading to high death rate in patients. Genomic instability (GI) is regarded as playing indispensable roles in tumorigenesis and impacting the prognosis of patients. The aberrant regulation of long non-coding RNAs (lncRNAs) is a main cause of GI. We combined the somatic mutation profiles and expression profiles to identify GI derived lncRNAs (GID-lncRNAs) in ccRCC and developed a GID-lncRNAs based risk signature for prognosis prediction and medication guidance.MethodsWe decided cases with top 25% cumulative number of somatic mutations as genomically unstable (GU) group and last 25% as genomically stable (GS) group, and identified differentially expressed lncRNAs (GID-lncRNAs) between two groups. Then we developed the risk signature with all overall survival related GID-lncRNAs with least absolute shrinkage and selection operator (LASSO) Cox regression. The functions of the GID-lncRNAs were partly interpreted by enrichment analysis. We finally validated the effectiveness of the risk signature in prognosis prediction and medication guidance.ResultsWe developed a seven-lncRNAs (LINC00460, AL139351.1, AC156455.1, AL035446.1, LINC02471, AC022509.2, and LINC01606) risk signature and divided all samples into high-risk and low-risk groups. Patients in high-risk group were in more severe clinicopathologic status (higher tumor grade, pathological stage, T stage, and more metastasis) and were deemed to have less survival time and lower survival rate. The efficacy of prognosis prediction was validated by receiver operating characteristic analysis. Enrichment analysis revealed that the lncRNAs in the risk signature mainly participate in regulation of cell cycle, DNA replication, material metabolism, and other vital biological processes in the tumorigenesis of ccRCC. Moreover, the risk signature could help assess the possibility of response to precise treatments.ConclusionOur study combined the somatic mutation profiles and the expression profiles of ccRCC for the first time and developed a GID-lncRNAs based risk signature for prognosis predicting and therapeutic scheme deciding. We validated the efficacy of the risk signature and partly interpreted the roles of the seven lncRNAs composing the risk signature in ccRCC. Our study provides novel insights into the roles of genomic instability derived lncRNAs in ccRCC.

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Section: Introductionmentioning

confidence: 99%

Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

Yang

Xiong

2021

Front. Oncol.

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“…The one-tailed Mann–Whitney U test P values are indicated in ( a ) and ( e ). The MATH 96 and DEPTH 97 algorithms were used to evaluate ITH at the DNA and mRNA levels, respectively. TMB tumor mutation burden, TAL tumor aneuploidy level, HRD homologous recombination deficiency, SCNAs somatic copy number alterations, OR odds ratio, ITH intratumor heterogeneity, ns, not significant, * P < 0.05, ** P < 0.01, *** P < 0.001.…”

Section: Resultsmentioning

confidence: 99%

“…TMB is the total count of non-synonymous somatic mutations in the tumor, and TAL is the tumor aneuploidy level evaluated by ABSOLUTE 95 . We used the MATH 96 and DEPTH 97 algorithms to evaluate ITH at the DNA and mRNA levels, respectively. The MATH ITH scores were calculated by using the function “math.score” 96 in the R package “maftools” with the input of “maf” files, and the DEPTH ITH scores were calculated by using the R package “DEPTH” with the input of gene expression profiles in tumor and normal tissues.…”

Section: Methodsmentioning

confidence: 99%

Identification of gastric cancer subtypes based on pathway clustering

Wang

2021

npj Precis. Onc.

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Gastric cancer (GC) is highly heterogeneous in the stromal and immune microenvironment, genome instability (GI), and oncogenic signatures. However, a classification of GC by combining these features remains lacking. Using the consensus clustering algorithm, we clustered GCs based on the activities of 15 pathways associated with immune, DNA repair, oncogenic, and stromal signatures in three GC datasets. We identified three GC subtypes: immunity-deprived (ImD), stroma-enriched (StE), and immunity-enriched (ImE). ImD showed low immune infiltration, high DNA damage repair activity, high tumor aneuploidy level, high intratumor heterogeneity (ITH), and frequent TP53 mutations. StE displayed high stromal signatures, low DNA damage repair activity, genomic stability, low ITH, and poor prognosis. ImE had strong immune infiltration, high DNA damage repair activity, high tumor mutation burden, prevalence of microsatellite instability, frequent ARID1A mutations, elevated PD-L1 expression, and favorable prognosis. Based on the expression levels of four genes (TAP2, SERPINB5, LTBP1, and LAMC1) in immune, DNA repair, oncogenic, and stromal pathways, we developed a prognostic model (IDOScore). The IDOScore was an adverse prognostic factor and correlated inversely with immunotherapy response in cancer. Our identification of new GC subtypes provides novel insights into tumor biology and has potential clinical implications for the management of GCs.

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“…(G) Spearman correlation between TMPRSS2 expression levels and intratumor heterogeneity (ITH) scores. The ITH scores were evaluated by the DEPTH algorithm [29].…”

Section: Resultsmentioning

confidence: 99%

“…Genomic instability can promote tumor heterogeneity, which is associated with tumor progression, immune evasion, and drug resistance [28]. We used the DEPTH algorithm [29] to score ITH for each TCGA-LUAD sample and found a significant negative correlation between TMPRSS2 expression levels and ITH scores in LUAD (ρ = -0.55; p < 0.001) (Figure 3G). It indicates a significant association between TMPRSS2 downregulation and increased ITH in LUAD.…”

Section: Resultsmentioning

confidence: 99%

The SARS-CoV-2 host cell membrane fusion protein TMPRSS2 is a tumor suppressor and its downregulation correlates with increased antitumor immunity and immunotherapy response in lung adenocarcinoma

Liu

Zhang

Feng

et al. 2021

Preprint

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Background TMPRSS2 is a host cell membrane fusion protein for SARS-CoV-2 invading human host cells. It also has an association with cancer, particularly prostate cancer. However, its association with lung cancer remains insufficiently explored. Thus, an in-depth investigation into the association between TMPRSS2 and lung cancer is significant, considering that lung cancer is the leading cause of cancer death and that the lungs are the primary organ SARS-CoV-2 attacks. Methods Using five lung adenocarcinoma (LUAD) genomics datasets, we explored associations between TMPRSS2 expression and immune signatures, cancer-associated pathways, tumor progression phenotypes, and clinical prognosis in LUAD by the bioinformatics approach. Furthermore, we validated the findings from the bioinformatics analysis by performing in vitro experiments with the human LUAD cell line A549 and in vivo experiments with mouse tumor models. We also validated our findings in LUAD patients from Jiangsu Cancer Hospital, China. Results TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD8+ T and NK cells and immune cytolytic activity in LUAD, which represent antitumor immune signatures. Meanwhile, TMPRSS2 expression levels were negatively correlated with the enrichment levels of CD4+ regulatory T cells and myeloid-derived suppressor cells and PD-L1 expression levels in LUAD, which represent antitumor immunosuppressive signatures. However, TMPRSS2 expression levels showed a significant positive correlation with the ratios of immune-stimulatory/immune-inhibitory signatures (CD8+ T cells/PD-L1) in LUAD. It indicated that TMPRSS2 levels had a stronger negative correlation with immune-inhibitory signatures than with immune-stimulatory signatures. TMPRSS2 downregulation correlated with elevated activities of many oncogenic pathways in LUAD, including cell cycle, mismatch repair, p53, and extracellular matrix (ECM) signaling. TMPRSS2 downregulation correlated with increased proliferation, stemness, genomic instability, tumor advancement, and worse survival in LUAD. In vitro and in vivo experiments validated the association of TMPRSS2 deficiency with increased tumor cell proliferation and invasion and antitumor immunity in LUAD. Moreover, in vivo experiments demonstrated that TMPRSS2-knockdown tumors were more sensitive to BMS-1, an inhibitor of PD-1/PD-L1. Conclusions TMPRSS2 is a tumor suppressor, while its downregulation is a positive biomarker of immunotherapy in LUAD. Our data provide a connection between lung cancer and pneumonia caused by SARS-CoV-2 infection.

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An algorithm to quantify intratumor heterogeneity based on alterations of gene expression profiles

Cited by 64 publications

References 67 publications

Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

Development and Interpretation of a Genomic Instability Derived lncRNAs Based Risk Signature as a Predictor of Prognosis for Clear Cell Renal Cell Carcinoma Patients

Identification of gastric cancer subtypes based on pathway clustering

The SARS-CoV-2 host cell membrane fusion protein TMPRSS2 is a tumor suppressor and its downregulation correlates with increased antitumor immunity and immunotherapy response in lung adenocarcinoma

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