Multi-omics approach to infer cancer therapeutic targets on chromosome 20q across tumor types

<p>The identification of good targets is a critical step for the development of targeted therapies for cancer treatment. Here, we used a multi-omics approach to delineate potential targets on chromosome 20q, which frequently shows a complex pattern of DNA copy number amplification in many human cancers suggesting the presence of multiple driver genes. By comparing the amounts of individual mRNAs in cancer from 11 different human tissues with those in their corresponding normal tissues, we identified 18 genes that were robustly elevated across human cancers. Moreover, we found that higher expression levels of a majority of these genes were associated with poor prognosis in many human cancer types. Using DNA copy number and expression data for all 18 genes obtained from The Cancer Genome Atlas project, we discovered that amplification is a major mechanism driving overexpression of these 18 genes in the majority of human cancers. Our integrated analysis suggests that 18 genes on chromosome 20q might serve as novel potential molecular targets for targeted cancer therapy.</p>

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Extensive protein dosage compensation in aneuploid human cancers

10.1101/2021.06.18.449005 ◽

2021 ◽

Author(s):

Klaske Marijke Schukken ◽

Jason Meyer Sheltzer

Keyword(s):

Protein Expression ◽

Dosage Compensation ◽

Copy Number ◽

Human Cancer ◽

Tumor Development ◽

Driver Genes ◽

Human Cancer Cell Lines ◽

Chromosome Copy Number ◽

Human Cancers ◽

Copy Number Changes

Aneuploidy is a hallmark of human cancers, but the effects of aneuploidy on protein expression remain poorly understood. To uncover how chromosome copy number changes influence the cancer proteome, we have conducted an analysis of hundreds of human cancer cell lines with matched copy number, RNA expression, and protein expression data. We found that a majority of proteins exhibit dosage compensation and fail to change by the degree expected based on chromosome copy number alone. We uncovered a variety of gene groups that were recurrently buffered upon both chromosome gain and loss, including protein complex subunits and cell cycle genes. Several genetic and biophysical factors were predictive of protein buffering, highlighting complex post-translational regulatory mechanisms that maintain appropriate gene product dosage. Finally, we established that chromosomal aneuploidy has an unexpectedly moderate effect on the expression of oncogenes and tumor suppressors, demonstrating that these key cancer drivers can be subject to dosage compensation as well. In total, our comprehensive analysis of aneuploidy and dosage compensation across cancers will help identify the key driver genes encoded on altered chromosomes and will shed light on the overall consequences of aneuploidy during tumor development.

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Comprehensive characterization and clinical relevance of the SWI/SNF copy number aberrations across human cancers

Hereditas ◽

10.1186/s41065-021-00203-y ◽

2021 ◽

Vol 158 (1) ◽

Author(s):

Zhiwei Xing ◽

Buhuan Ma ◽

Weiting Sun ◽

Yimin Sun ◽

Caixia Liu

Keyword(s):

Copy Number ◽

Human Cancer ◽

Therapy Resistance ◽

The Cancer Genome Atlas ◽

Dna Damage And Repair ◽

Human Cancers ◽

Oncogenic Pathways ◽

Cancer Types ◽

Tcga Dataset ◽

The Impact

Abstract Background Alterations in genes encoding chromatin regulatory proteins are prevalent in cancers and may confer oncogenic properties and molecular changes linked to therapy resistance. However, the impact of copy number alterations (CNAs) of the SWItch/Sucrose NonFermentable (SWI/SNF) complex on the oncogenic and immunologic properties has not been systematically explored across human cancer types. Methods We comprehensively analyzed the genomic, transcriptomic and clinical data of The Cancer Genome Atlas (TCGA) dataset across 33 solid cancers. Results CNAs of the SWI/SNF components were identified in more than 25% of all queried cancers, and tumors harboring SWI/SNF CNAs demonstrated a worse overall survival (OS) than others in several cancer types. Mechanistically, the SCNA events in the SWI/SNF complex are correlated with dysregulated genomic features and oncogenic pathways, including the cell cycle, DNA damage and repair. Notably, the SWI/SNF CNAs were associated with homologous recombination deficiency (HRD) and improved clinical outcomes of platinum-treated ovarian cancer. Furthermore, we observed distinct immune infiltrating patterns and immunophenotypes associated with SWI/SNF CNAs in different cancer types. Conclusion The CNA events of the SWI/SNF components are a key process linked to oncogenesis, immune infiltration and therapeutic responsiveness across human cancers.

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Predicting STAT1 as a prognostic marker in patients with solid cancer

Therapeutic Advances in Medical Oncology ◽

10.1177/1758835920917558 ◽

2020 ◽

Vol 12 ◽

pp. 175883592091755

Author(s):

Jinguo Zhang ◽

Fanchen Wang ◽

Fangran Liu ◽

Guoxiong Xu

Keyword(s):

Ovarian Cancer ◽

Prognostic Value ◽

Renal Carcinoma ◽

The Cancer Genome Atlas ◽

Solid Cancer ◽

Lower Grade ◽

High Grade ◽

Large Tumor ◽

Normal Tissues ◽

Tumor Types

Background: Aberrant activities of signal transducer and activator of transcription 1 (STAT1) have been implicated in cancer development. However, the prognostic value of STAT1 remains unclear. This report identified the role of STAT1 in prognosis in patients with solid cancer through open literature and The Cancer Genome Atlas (TCGA) database. Methods: Published articles were obtained from PubMed, Web of Science, and Embase databases according to a search strategy up to October 2019. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were extracted to assess the prognostic factors of patients. TCGA datasets were used to explore the prognostic value of STAT1 in various cancers. Results: A total of 15 studies incorporating 2839 patients with solid cancers were included. Pooled data showed that overexpressed STAT1 favored long overall survival (OS) (HR = 0.604, 95% CI = 0.431–0.846, p = 0.003) and disease-specific survival (DSS) (HR = 0.650, 95% CI = 0.512–0.825, p = 0.000). In subgroup analyses, highly expressed STAT1 was correlated with long OS of patients with high-grade serous ovarian cancer and oral squamous cell carcinoma. Data extracted from TCGA datasets unveiled that STAT1 expression was significantly higher in 12 cancers (e.g. bladder and breast) than their adjacent normal tissues. Again, highly expressed STAT1 favored long OS of patients with ovarian cancer as well as rectum adenocarcinoma, sarcoma, and skin cutaneous melanoma. However, in renal carcinoma, brain lower grade glioma, lung adenocarcinoma, and pancreatic cancer, highly expressed STAT1 was correlated with poor OS of patients. Particularly in renal carcinoma, increased STAT1 expression was associated with high grade, later stage, large tumor size, and lymph node and distant metastasis. Conclusion: STAT1 has been identified to have prognostic value in patients with solid cancer. Highly expressed STAT1 may predict prognosis in cancer patients based on their tumor types.

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Mitochondrial DNA Copy Number Alterations in Human Cancers

Encyclopedia of Life Sciences ◽

10.1002/9780470015902.a0024873 ◽

2012 ◽

Cited By ~ 1

Author(s):

Man Yu

Keyword(s):

Mitochondrial Dna ◽

Copy Number ◽

Copy Number Alterations ◽

Dna Copy Number ◽

Human Cancers ◽

Mitochondrial Dna Copy Number ◽

Dna Copy Number Alterations

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The Gasdermin E gene Potential as a Pan-Cancer Biomarker, While Discriminating between Different Tumor Types

Cancers ◽

10.3390/cancers11111810 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1810 ◽

Cited By ~ 3

Author(s):

Joe Ibrahim ◽

Ken Op de Beeck ◽

Erik Fransen ◽

Marc Peeters ◽

Guy Van Camp

Keyword(s):

The Cancer Genome Atlas ◽

Tumor Type ◽

E Gene ◽

Normal Tissues ◽

Incidence And Mortality ◽

Cancer Genome Atlas ◽

Cancer Setting ◽

Tumor Types ◽

Methylation Patterns ◽

Pan Cancer

Due to the elevated rates of incidence and mortality of cancer, early and accurate detection is crucial for achieving optimal treatment. Molecular biomarkers remain important screening and detection tools, especially in light of novel blood-based assays. DNA methylation in cancer has been linked to tumorigenesis, but its value as a biomarker has not been fully explored. In this study, we have investigated the methylation patterns of the Gasdermin E gene across 14 different tumor types using The Cancer Genome Atlas (TCGA) methylation data (N = 6502). We were able to identify six CpG sites that could effectively distinguish tumors from normal samples in a pan-cancer setting (AUC = 0.86). This combination of pan-cancer biomarkers was validated in six independent datasets (AUC = 0.84–0.97). Moreover, we tested 74,613 different combinations of six CpG probes, where we identified tumor-specific signatures that could differentiate one tumor type versus all the others (AUC = 0.79–0.98). In all, methylation patterns exhibited great variation between cancer and normal tissues, but were also tumor specific. Our analyses highlight that a Gasdermin E methylation biomarker assay, not only has the potential for being a methylation-specific pan-cancer detection marker, but it also possesses the capacity to discriminate between different types of tumors.

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SNORA71A Promotes Colorectal Cancer Cell Proliferation, Migration, and Invasion

BioMed Research International ◽

10.1155/2020/8284576 ◽

2020 ◽

Vol 2020 ◽

pp. 1-11

Author(s):

Zhengxiang Zhang ◽

Yunxiang Tao ◽

Qingling Hua ◽

Juan Cai ◽

Xiaobing Ye ◽

...

Keyword(s):

Colorectal Cancer ◽

Cell Proliferation ◽

Sensory Perception ◽

The Cancer Genome Atlas ◽

Migration And Invasion ◽

Integrated Analysis ◽

Small Rna Sequencing ◽

Chemical Stimulus ◽

Normal Tissues

Small nucleolar RNAs (snoRNAs) play a crucial role during colorectal cancer (CRC) development. The study of SNORA71A is few, and its role in CRC is unknown. This study focused on screening abnormal snoRNAs in CRC and exploring the role of key snoRNA in CRC. The expression pattern of snoRNAs in 3 CRC and 3 normal colon tissues was detected via small RNA sequencing. The six candidate snoRNAs were identified by quantitative PCR (qPCR). Subsequently, the expression level of SNORA71A was further verified through the Cancer Genome Atlas (TCGA) data analysis and qPCR. The CCK8 and transwell assays were used to detect the functional role of SNORA71A in CRC cells. The integrated analysis of snoRNA expression profile indicated that a total 107 snoRNAs were significantly differentially expressed (DE) in CRC tissues compared with normal tissues, including 45 upregulated and 62 downregulated snoRNAs. Bioinformatics analysis revealed that the DE snoRNAs were mainly implicated in “detection of chemical stimulus involved in sensory perception of smell” and “sensory perception of smell” in the biological process. The DE snoRNAs were preferentially enriched in “olfactory transduction” and “glycosphingolipid biosynthesis-ganglio series pathway.” The expression of SNORA71A was upregulated in CRC tissues and cells. SNORA71A expression showed statistically significant correlations with TNM stage ( P = 0.0196 ) and lymph node metastasis ( P = 0.0189 ) and can serve as biomarkers for CRC. Importantly, SNORA71A significantly facilitated the CRC cell proliferation, migration, and invasion. Our findings indicate that SNORA71A screened by sequencing acted as an oncogene and promoted proliferation, migration, and invasion ability of CRC cells.

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Data Fusion Techniques for the Integration of Multi-Domain Genomic Data from Uveal Melanoma

Cancers ◽

10.3390/cancers11101434 ◽

2019 ◽

Vol 11 (10) ◽

pp. 1434 ◽

Cited By ~ 1

Author(s):

Max Pfeffer ◽

André Uschmajew ◽

Adriana Amaro ◽

Ulrich Pfeffer

Keyword(s):

Gene Expression ◽

Data Fusion ◽

Uveal Melanoma ◽

Copy Number ◽

Somatic Mutations ◽

Genomic Data ◽

The Cancer Genome Atlas ◽

Driver Genes ◽

Discrimination Power ◽

Value Decomposition

Uveal melanoma (UM) is a rare cancer that is well characterized at the molecular level. Two to four classes have been identified by the analyses of gene expression (mRNA, ncRNA), DNA copy number, DNA-methylation and somatic mutations yet no factual integration of these data has been reported. We therefore applied novel algorithms for data fusion, joint Singular Value Decomposition (jSVD) and joint Constrained Matrix Factorization (jCMF), as well as similarity network fusion (SNF), for the integration of gene expression, methylation and copy number data that we applied to the Cancer Genome Atlas (TCGA) UM dataset. Variant features that most strongly impact on definition of classes were extracted for biological interpretation of the classes. Data fusion allows for the identification of the two to four classes previously described. Not all of these classes are evident at all levels indicating that integrative analyses add to genomic discrimination power. The classes are also characterized by different frequencies of somatic mutations in putative driver genes (GNAQ, GNA11, SF3B1, BAP1). Innovative data fusion techniques confirm, as expected, the existence of two main types of uveal melanoma mainly characterized by copy number alterations. Subtypes were also confirmed but are somewhat less defined. Data fusion allows for real integration of multi-domain genomic data.

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