Dataset Information

Gene expression profiling for the diagnosis of multiple primary malignant tumors.

ABSTRACT:

Background

The incidence of multiple primary malignant tumors (MPMTs) is rising due to the development of screening technologies, significant treatment advances and increased aging of the population. For patients with a prior cancer history, identifying the tumor origin of the second malignant lesion has important prognostic and therapeutic implications and still represents a difficult problem in clinical practice.

Methods

In this study, we evaluated the performance of a 90-gene expression assay and explored its potential diagnostic utility for MPMTs across a broad spectrum of tumor types. Thirty-five MPMT patients from Sir Run Run Shaw Hospital, College of Medicine, Zhejiang University and Fudan University Shanghai Cancer Center were enrolled; 73 MPMT specimens met all quality control criteria and were analyzed by the 90-gene expression assay.

Results

For each clinical specimen, the tumor type predicted by the 90-gene expression assay was compared with its pathological diagnosis, with an overall accuracy of 93.2% (68 of 73, 95% confidence interval 0.84-0.97). For histopathological subgroup analysis, the 90-gene expression assay achieved an overall accuracy of 95.0% (38 of 40; 95% CI 0.82-0.99) for well-moderately differentiated tumors and 92.0% (23 of 25; 95% CI 0.82-0.99) for poorly or undifferentiated tumors, with no statistically significant difference (p-value?>?0.5). For squamous cell carcinoma specimens, the overall accuracy of gene expression assay also reached 87.5% (7 of 8; 95% CI 0.47-0.99) for identifying the tumor origins.

Conclusions

The 90-gene expression assay provides flexibility and accuracy in identifying the tumor origin of MPMTs. Future incorporation of the 90-gene expression assay in pathological diagnosis will assist oncologists in applying precise treatments, leading to improved care and outcomes for MPMT patients.

SUBMITTER: Zheng Y

PROVIDER: S-EPMC7846996 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

Gene expression profiling for the diagnosis of multiple primary malignant tumors.

Zheng Yu Y Sun Yifeng Y Kuai Yue Y Fu Guoxiang G An Huimin H Chen Jinyun J Chen Jinying J Zhu Jiajun J Wo Yixin Y Wu Yiwang Y Song Kaibin K Xu Qinghua Q Xu Qinghua Q Wu Di D Huang Deshuang D Wang Qifeng Q Pan Hongming H

Cancer cell international 20210112 1

<h4>Background</h4>The incidence of multiple primary malignant tumors (MPMTs) is rising due to the development of screening technologies, significant treatment advances and increased aging of the population. For patients with a prior cancer history, identifying the tumor origin of the second malignant lesion has important prognostic and therapeutic implications and still represents a difficult problem in clinical practice.<h4>Methods</h4>In this study, we evaluated the performance of a 90-gene e ...[more]

PMID: 33514366

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Project description:Background: Breast cancer is a complex disease, encompassed by different clinically and molecularly stratified entities. In 2000, Perou and colleagues demonstrated that tumor phenotypic diversity correlates with differences in global gene expression patterns, which in turn reflect aspects of the biological behavior of the tumors. Gene expression profiling has distinguished sporadic breast tumor sub-classes with genetic, histopathological and clinical differences, however, little is known about the molecular classification of hereditary breast tumors. It has been recently suggested that most tumors arising in BRCA1 mutation carriers display a basal-like phenotype, with the percentages reported in different studies ranging from 44 to almost 100%. In the present study we used expression profiling to produce a molecular classification of BRCA1-associated breast tumors and applied an integrative approach to examine biological dependencies or differences. Methods and Findings: We used frozen tumor tissue from fourteen patients all of which harbored germline pathological mutations in BRCA1. Total RNA extraction, amplification and labeling with Cy5 were performed using standard protocols. Universal Human Reference RNA (Stratagene) was used as a reference and labeled with Cy3. Each pair of Cy3/Cy5 samples was hybridized onto the CNIO human OncoChip V2, which consists of a spotted microarray with 11,675 cDNA clones from the I.M.A.G.E. Consortium. Two channel ratios (Cy5/Cy3) for each spot were generated and quantified using GenePix Pro 5.1 (Axon Instruments, Inc., Union City, CA, USA). Data were normalized and filtered and multiple statistical analyses were performed. The data are deposited in the GEO database under the accession number GSE12350. A tissue microarray (TMA) containing an independent series of 15 BRCA1 tumors was used to validate some of the results obtained. We have described molecular signatures that define BRCA1 subclasses depending on the expression of the gene encoding for Estrogen Receptor, ESR1. Signatures were found to be molecularly associated with different biological processes and transcriptional regulatory programs. The signature of ESR1-positive tumors was mainly linked to cell proliferation-related processes and, therefore, regulated by the estrogen receptor, while the signature of ESR1-negative tumors was mainly linked to the immune response and possibly regulated by transcription factors of the REL/NFκB family. These signatures were then verified in an independent series of hereditary and sporadic breast tumors, which revealed a possible prognostic value for each subclass. Over-expression of immune response genes appears to be a common feature of ER-negative sporadic and hereditary breast cancer and is associated with good prognosis. Interestingly, the ESR1-negative tumors were sub-stratified into two groups presenting light differences in the magnitude of the expression of immune response transcripts and REL/NFκB transcription factors, and this could be dependent on the type of germline alteration. In addition, analysis of the human protein-protein interaction network provides the wiring diagram of critical molecular associations in BRCA1 tumorigenesis and identifies close relationships between the different signatures. Conclusions: In summary, in the present study we have established the gene expression profiling of a series of BRCA1 tumors and found that there is a further degree of heterogeneity beyond the main classification by the expression of ESR1 and the presence or absence of a basal-like phenotype. We have identified specific signatures for ESR1-positive and ESR1-negative BRCA1 tumors, the latter characterized by the enrichment of immune response and cell cycle genes, and have found that slight differences in the level of expression of the immune response stratify the ESR1-negative BRCA1 tumors into two additional sub-groups (A and B) with possible prognostic differences. NFkB could be a major driver responsible for the levels of both immune response and apoptotic genes in this group of tumors, which could in turn be related to the type of germline mutation in BRCA1. This study reveals the molecular complexity of BRCA1 breast tumors, which are found to display similarities to sporadic tumors, and suggests possible prognostic implications. 14 samples (primary breast tumors containing a BRCA1 mutation) were hybridized to a cDNA microarray in order to investigate the possible heterogeneity within the BRCA1 group.

Dataset Information

Gene expression profiling for the diagnosis of multiple primary malignant tumors.

Background

Methods

Results

Conclusions

Publications

Gene expression profiling for the diagnosis of multiple primary malignant tumors.

Similar Datasets

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