Identification of driver copy number alterations in diverse cancer types and application in drug repositioning

Combined single cell and spatial transcriptome analysis reveals cellular heterogeneity of hedgehog pathway in gastric cancer

Gastric cancer (GC) is one of the most common and deadly malignancies in the world. Abnormal activation of hedgehog pathway is closely related to tumor development and progression. However, potential therapeutic targets for GC based on the hedgehog pathway have not been clearly identified. In the present study, we combined single-cell sequencing data and spatial transcriptomics to deeply investigate the role of hedgehog pathway in GC. Based on a comprehensive scoring algorithm, we found that fibroblasts from GC tumor tissues were characterized by a highly enriched hedgehog pathway. By analyzing the development process of fibroblasts, we found that CCND1 plays an important role at the end stage of fibroblast development, which may be related to the formation of tumor-associated fibroblasts. Based on spatial transcriptome data, we deeply mined the role of CCND1 in fibroblasts. We found that CCND1-negative and -positive fibroblasts have distinct characteristics. Based on bulk transcriptome data, we verified that highly infiltrating CCND1 + fibroblasts are a risk factor for GC patients and can influence the immune and chemotherapeutic efficacy of GC patients. Our study provides unique insights into GC and hedgehog pathways and also new directions for cancer treatment strategies.

SOX2-OT Binds with ILF3 to Promote Head and Neck Cancer Progression by Modulating Crosstalk between STAT3 and TGF-β Signaling

Long non-coding RNA (lncRNA) is involved in the progression of head and neck squamous cell carcinoma (HNSCC). The molecular mechanism of lncRNA SOX2-OT in HNSCC remains unclear. Therefore, we aimed to elucidate the oncogenic role of SOX2-OT in HNSCC. QRT-PCR analysis was performed in 61 pairs of HNSCC cancer tissues, adjacent normal tissues, and 68 plasma samples confirmed that lncRNA SOX2-OT was overexpressed in cancer tissues and plasma samples, which served as a poor prognostic factor for HNSCC. The FISH assay demonstrated that SOX2-OT was localized in the nucleus and cytoplasm of HNSCC cell lines. Further, the cell function assay confirmed that SOX2-OT promoted cell proliferation and metastasis in vitro and in vivo. RNA pulldown and RIP assay results revealed that SOX2-OT bonds with ILF3 in HNSCC, and the rescue assay confirmed that SOX2-OT played an oncogenic role depending on ILF3 protein expression. Ingenuity pathway analysis and Western blotting indicated that SOX2-OT regulated HNSCC progression by promoting STAT3 phosphorylation and modulating the crosstalk between STAT3 and TGF-β signaling. These results reveal evidence for the role of SOX2-OT in HNSCC progression and metastasis by binding to ILF3, which may serve as a therapeutic target and prognostic biomarker in HNSCC.

Long non-coding RNA PVT1 (PVT1) affects the expression of CCND1 and promotes doxorubicin resistance in osteosarcoma cells

Background

Acquired drug-resistance is the major risk factor for poor prognosis and short-term survival in patients with osteosarcoma (OS). Accumulating evidence has revealed that long noncoding RNAs (lncRNAs), including plasmacytoma variant translocation 1 (PVT1), play potential regulatory roles in the malignant development of OS. Considering the subcellular distribution of PVT1 as both nuclear and cytoplasmic lncRNA, a thorough exploration of its extensive mechanisms becomes essential.

Methods

The GEO database was utilized for the acquisition of gene expression data, which was subsequently analyzed to fulfill the research objectives. The subcellular localization of PVT1 in OS cells was determined using fluorescence in situ hybridization (FISH) and quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, the sensitivity of OS cells to doxorubicin was comprehensively evaluated through measurements of cell viability, site-specific proliferation capacity, and the relative expression abundance of multidrug resistance-related proteins (MRPs). In order to investigate the differential response of OS cells with varying levels of PVT1 expression to doxorubicin, pulmonary metastasis mice models were established for in vivo studies. Molecular interactions were further examined using the dual-luciferase assay and RNA immunoprecipitation assay (RIP) to analyze the binding sites of miR-15a-5p and miR-15b-5p on PVT1 and G1/S-specific cyclinD1 (CCND1) mRNA. Furthermore, the chromatin immunoprecipitation (ChIP) and dual-luciferase assay were employed to assess the transcriptional activation of the proto-oncogene c-myc (MYC) on the CCND1 promoter and identify the corresponding binding sites.

Results

In doxorubicin resistant OS cells, transcription levels of PVT1, MYC and CCND1 were significantly higher than those in original cells. In vivo experiments demonstrated that OS cells rich in PVT1 expression exhibited enhanced tumorigenicity and resistance to doxorubicin. In vitro experiments, it has been observed that overexpression of PVT1 in OS cells is accompanied by an upregulation of CCND1, thereby facilitating resistance to doxorubicin. Nonetheless, this PVT1-induced resistance can be effectively attenuated by the knockdown of CCND1. Mechanistically, PVT1 functions as a competitive endogenous RNA (ceRNA) that influences the expression of CCND1 by inhibiting the degradation function of miR-15a-5p and miR-15b-5p on CCND1 mRNA. Additionally, as a neighboring gene of MYC, PVT1 plays a role in maintaining MYC protein stability, which further enhances MYC-dependent CCND1 transcriptional activity.

Conclusion

The resistance of OS cells to doxorubicin is facilitated by PVT1, which enhances the expression of CCND1 through a dual mechanism. This findings offer a novel perspective for comprehending the intricate regulatory mechanisms of long non-coding RNA in influencing the expression of coding genes.

Molecular characterization of early breast cancer onset to understand disease phenotypes in African patients

Female breast cancer (BC) is the leading cause of cancer-related deaths worldwide with higher mortality rates and early onset in developing countries. The molecular basis of early disease onset is still elusive. We recruited 472 female breast cancer from two sub-Saharan African countries (Cameroon and Congo) between 2007 and 2018 and collected clinical data from these patients. To investigate the molecular drivers of early disease onset, we analyzed publicly available breast cancer molecular data from the cancer genome atlas (TCGA) and the gene expression omnibus (GEO) for copy number alteration, mutation and gene expression. Early BC onset (EOBRCA) (diagnosis before 45 years) was higher in African women compared with the TCGA cohort (51.7% vs 15.6%). The tumor grade, mitotic index, HER2 + phenotype, basal-like phenotype and ki67 were higher in EOBRCA for all cohorts. BC risk factors such as parity, breastfeeding early onset of menarche and use of hormonal contraceptives were significantly associated with EOBRCA (p < 0.05). EOBRCA was equally associated with copy number alterations in several oncogenes including CDH6 and FOXM1 and tumor suppressor including TGM3 and DMBT1 as well as higher TP53 mutation rates (OR: 2.93, p < 0.01). There was a significant enrichment of TGFß signaling in EOBRCA with TGM3 deletions, which was associated with high expression of all SMAD transcription factors as well as WNT ligands. The Frizzled receptors FZD1, FZD4 and FZD6 were significantly upregulated in EOBRCA, suggesting activation of non-canonical WNT signaling. Our data, suggest the implication of TGM3 deletion in early breast cancer onset. Further molecular investigations are warranted in African patients.

Identifying Key Somatic Copy Number Alterations Driving Dysregulation of Cancer Hallmarks in Lower-Grade Glioma

Somatic copy-number alterations (SCNAs) are major contributors to cancer development that are pervasive and highly heterogeneous in human cancers. However, the driver roles of SCNAs in cancer are insufficiently characterized. We combined network propagation and linear regression models to design an integrative strategy to identify driver SCNAs and dissect the functional roles of SCNAs by integrating profiles of copy number and gene expression in lower-grade glioma (LGG). We applied our strategy to 511 LGG patients and identified 98 driver genes that dysregulated 29 cancer hallmark signatures, forming 143 active gene-hallmark pairs. We found that these active gene-hallmark pairs could stratify LGG patients into four subtypes with significantly different survival times. The two new subtypes with similar poorest prognoses were driven by two different gene sets (one including EGFR, CDKN2A, CDKN2B, INFA8, and INFA5, and the other including CDK4, AVIL, and DTX3), respectively. The SCNAs of the two gene sets could disorder the same cancer hallmark signature in a mutually exclusive manner (including E2F_TARGETS and G2M_CHECKPOINT). Compared with previous methods, our strategy could not only capture the known cancer genes and directly dissect the functional roles of their SCNAs in LGG, but also discover the functions of new driver genes in LGG, such as IFNA5, IFNA8, and DTX3. Additionally, our method can be applied to a variety of cancer types to explore the pathogenesis of driver SCNAs and improve the treatment and diagnosis of cancer.

Genetic alterations associated with multiple primary malignancies

Breast cancer (BC) patients are frequently at risk of developing other malignancies following treatment. Although studies have been conducted to elucidate the etiology of multiple primary malignancies (MPM) after a BC diagnosis, few studies have investigated other previously diagnosed primary malignancies (OPPM) before BC. Here, genome‐wide profiling was used to identify potential driver DNA copy number alterations and somatic mutations that promote the development of MPMs. To compare the genomic profiles for two primary tumors (BC and OPPM) from the same patient, tumor pairs from 26 young women (≤50 years) diagnosed with one or more primary malignancies before breast cancer were analyzed. Malignant melanoma was the most frequent OPPM, followed by gynecologic‐ and hematologic malignancies. However, significantly more genetic alterations were detected in BC compared to the OPPM. BC also showed more genetic similarity as a group than the tumor pairs. Clonality testing showed that genetic alterations on chromosomes 1, 3, 16, and 19 were concordant in both tumors in 13 patients. TP53 mutations were also found to be prevalent in BC, MM, and HM. Although all samples were classified as genetically unstable, chromothripsis‐like patterns were primarily observed in BC. Taken together, few recurrent genetic alterations were identified in both tumor pairs that can explain the development of MPMs in the same patient. However, larger studies are warranted to further investigate key driver mutations associated with MPMs.

TPQCI: A topology potential-based method to quantify functional influence of copy number variations

Copy number variation (CNV) is a major type of chromosomal structural variation that play important roles in many diseases including cancers. Due to genome instability, a large number of CNV events can be detected in diseases such as cancer. Therefore, it is important to identify the functionally important CNVs in diseases, which currently still poses a challenge in genomics. One of the critical steps to solve the problem is to define the influence of CNV. In this paper, we provide a topology potential based method, TPQCI, to quantify this kind of influence by integrating statistics, gene regulatory associations, and biological function information. We used this metric to detect functionally enriched genes on genomic segments with CNV in breast cancer and multiple myeloma and discovered biological functions influenced by CNV. Our results demonstrate that, by using our proposed TPQCI metric, we can detect disease-specific genes that are influenced by CNVs. Source codes of TPQCI are provided in Github (https://github.com/usos/TPQCI).

Disease-Causing Mutations and Rearrangements in Long Non-coding RNA Gene Loci

The classic understanding of molecular disease-mechanisms is largely based on protein-centric models. During the past decade however, genetic studies have identified numerous disease-loci in the human genome that do not encode proteins. Such non-coding DNA variants increasingly gain attention in diagnostics and personalized medicine. Of particular interest are long non-coding RNA (lncRNA) genes, which generate transcripts longer than 200 nucleotides that are not translated into proteins. While most of the estimated ~20,000 lncRNAs currently remain of unknown function, a growing number of genetic studies link lncRNA gene aberrations with the development of human diseases, including diabetes, AIDS, inflammatory bowel disease, or cancer. This suggests that the protein-centric view of human diseases does not capture the full complexity of molecular patho-mechanisms, with important consequences for molecular diagnostics and therapy. This review illustrates well-documented lncRNA gene aberrations causatively linked to human diseases and discusses potential lessons for molecular disease models, diagnostics, and therapy.

lncRNAHIF1A-AS2 Promotes Renal Carcinoma Cell Proliferation and Migration via miR-130a-5p/ERBB2 Pathway

Background

Long non-coding RNAs (lncRNAs) are essential for tumorigenesis and progression of diverse cancers. This study aims to investigate the roles of lncRNAs on renal carcinoma.

Methods

The expression of lncRNA HIF1A-AS2 in clear cell renal cell carcinoma (ccRCC) and adjacent non-cancer tissues was identified by quantitative real-time PCR (qRT-PCR). Investigations were performed on biological function of lncRNA HIF1A-AS2 on cell proliferation, cell cycle, apoptosis and invasion of ccRCC by overexpression and knockdown experiments. Further, luciferase reporter assay and Western blot were constructed to explore molecular mechanisms underlying the function of lncRNA HIF1A-AS2.

Results

HIF1A-AS2 was highly expressed in kidney cancer tissues and ccRCC cells. Interference of HIF1A-AS2 in vivo hindered cell proliferation, invasion and migration while accelerated cell apoptosis. Overexpression of HIF1A-AS2 presented an opposite effect that repressed the expression of miR-130a-5p, and miR-130a-5p inhibited the expression of HIF1A-AS2. Additionally, rescue experiments exhibited that oncogenic function of HIF1A-AS2 was partially dependent on the suppression of miR-130a-5p.

Conclusion

Our results indicated a critical role for the HIF1A-AS2-miR-130a-5p axis in renal carcinoma progression, which may act as a promising diagnostic biomarker and a pivotal therapeutic target for renal carcinoma cures.

Dissecting the Functional Mechanisms of Somatic Copy-Number Alterations Based on Dysregulated ceRNA Networks across Cancers

Somatic copy-number alterations (SCNAs) drive tumor growth and evolution. However, the functional roles of SCNAs across the genome are still poorly understood. We provide an integrative strategy to characterize the functional roles of driver SCNAs in cancers based on dysregulated competing endogenous RNA (ceRNA) networks. We identified 44 driver SCNAs in lower-grade glioma (LGG). The dysregulated patterns losing all correlation relationships dominated dysregulated ceRNA networks. Homozygous deletion of six genes in 9p21.3 characterized an LGG subtype with poor prognosis and contributed to the dysfunction of cancer-associated pathways in a complementary way. The pan-cancer analysis showed that different cancer types harbored different driver SCNAs through dysregulating the crosstalk with common ceRNAs. The same SCNAs destroyed their ceRNA networks through different miRNA-mediated ceRNA regulations in different cancers. Additionally, some SCNAs performed different functional mechanisms in different cancers, which added another layer of complexity to cancer heterogeneity. Compared with previous methods, our strategy could directly dissect functional roles of SCNAs from the view of ceRNA networks, which not only complemented the functions of protein-coding genes but also provided a new avenue to characterize the functions of noncoding RNAs. Also, our strategy could be applied to more types of cancers to identify pathogenic mechanism driven by the SCNAs.

Comprehensive Genomic Review of TCGA Head and Neck Squamous Cell Carcinomas (HNSCC)

The aim of this present study was to comprehensively describe somatic DNA alterations and transcriptional alterations in the last extension of the HNSCC subsets in TCGA, encompassing a total of 528 tumours. In order to achieve this goal, transcriptional analysis, functional enrichment assays, survival analysis, somatic copy number alteration analysis and somatic alteration analysis were carried out. A total of 3491 deregulated genes were found in HNSCC patients, and the functional analysis carried out determined that tissue development and cell differentiation were the most relevant signalling pathways in upregulated and downregulated genes, respectively. Somatic copy number alteration analysis showed a “top five” altered HNSCC genes: CDKN2A (deleted in 32.03% of patients), CDKN2B (deleted in 28.34% of patients), PPFIA1 (amplified in 26.02% of patients), FADD (amplified in 25.63% of patients) and ANO1 (amplified in 25.44% of patients). Somatic mutations analysis revealed TP53 mutation in 72% of the tumour samples followed by TTN (39%), FAT1 (23%) and MUC16 (19%). Another interesting result is the mutual exclusivity pattern that was discovered between the TP53 and PIK3CA mutations, and the co-occurrence of CDKN2A with the TP53 and FAT1 alterations. On analysis to relate differential expression genes and somatic copy number alterations, some genes were overexpressed and amplified, for example, FOXL2, but other deleted genes also showed overexpression, such as CDKN2A. Survival analysis revealed that overexpression of some oncogenes, such as EGFR, CDK6 or CDK4 were associated with poorer prognosis tumours. These new findings help us to develop new therapies and programs for the prevention of HNSCC.

ΔNp63 in squamous cell carcinoma: defining the oncogenic routes affecting epigenetic landscape and tumour microenvironment

Squamous cell carcinoma (SCC) is a treatment‐refractory tumour which arises from the epithelium of diverse anatomical sites such as oesophagus, head and neck, lung and skin. Accumulating evidence has revealed a number of genomic, clinical and molecular features commonly observed in SCC of distinct origins. Some of these genetic events culminate in fostering the activity of ΔNp63, a potent oncogene which exerts its pro‐tumourigenic effects by regulating specific transcriptional programmes to sustain malignant cell proliferation and survival. In this review, we will describe the genetic and epigenetic determinants underlying ΔNp63 oncogenic activities in SCC, and discuss some relevant transcriptional effectors of ΔNp63, emphasizing their impact in modulating the crosstalk between tumour cells and tumour microenvironment (TME).

Identification of cancer prognosis-associated lncRNAs based on the miRNA-TF co-regulatory motifs and dosage sensitivity

By integrating dosage sensitivity and motif regulation data, we established a framework and identified a total of 33 cancer prognosis-associated lncRNAs.

Copy number aberrations from Affymetrix SNP 6.0 genotyping data-how accurate are commonly used prediction approaches?

Copy number aberrations (CNAs) are known to strongly affect oncogenes and tumour suppressor genes. Given the critical role CNAs play in cancer research, it is essential to accurately identify CNAs from tumour genomes. One particular challenge in finding CNAs is the effect of confounding variables. To address this issue, we assessed how commonly used CNA identification algorithms perform on SNP 6.0 genotyping data in the presence of confounding variables. We simulated realistic synthetic data with varying levels of three confounding variables-the tumour purity, the length of a copy number region and the CNA burden (the percentage of CNAs present in a profiled genome)-and evaluated the performance of OncoSNP, ASCAT, GenoCNA, GISTIC and CGHcall. Furthermore, we implemented and assessed CGHcall*, an adjusted version of CGHcall accounting for high CNA burden. Our analysis on synthetic data indicates that tumour purity and the CNA burden strongly influence the performance of all the algorithms. No algorithm can correctly find lost and gained genomic regions across all tumour purities. The length of CNA regions influenced the performance of ASCAT, CGHcall and GISTIC. OncoSNP, GenoCNA and CGHcall* showed little sensitivity. Overall, CGHcall* and OncoSNP showed reasonable performance, particularly in samples with high tumour purity. Our analysis on the HapMap data revealed a good overlap between CGHcall, CGHcall* and GenoCNA results and experimentally validated data. Our exploratory analysis on the TCGA HNSCC data revealed plausible results of CGHcall, CGHcall* and GISTIC in consensus HNSCC CNA regions. Code is available at https://github.com/adspit/PASCAL.

Positive Caricature Transcriptomic Effects Associated with Broad Genomic Aberrations in Colorectal Cancer

We re-examined the correlation between Broad Genomic Aberrations (BGAs) and transcriptomic profiles in Colorectal Cancer (CRC). Two types of BGAs have been examined: Broad Copy-Number Abnormal regions (BCNAs), distinguished in gain- and loss-type, and Copy-Neutral Loss of Heterozygosities (CNLOHs). Transcripts are classified as “OverT” or “UnderT” if overexpressed or underexpressed comparing CRCs bearing a specific BGA to CRCs not bearing it and as “UpT” or “DownT” if upregulated or downregulated in cancer compared to normal tissue. BGA-associated effects were evaluated by changes in the “Chromosomal Distribution Index” (CDI) of different transcript classes. Data show that UpT are more sensitive than DownT to BCNA-associated gene dosage effects. “Over-UpT” genes are upregulated in cancer and further overexpressed by gene dosage, defining the so called “positive caricature transcriptomic effect”. When Over-UpT genes are ranked according to overexpression, top positions are occupied by genes implicated at the functional and therapeutic level in CRC. We show that cancer-upregulated transcripts are sensitive markers of BCNA-induced effects and suggest that analysis of positive caricature transcriptomic effects can provide clues toward the identification of BCNA-associated cancer driver genes.

A pan-cancer atlas of cancer hallmark-associated candidate driver lncRNAs

Substantial cancer genome sequencing efforts have discovered many important driver genes contributing to tumorigenesis. However, very little is known about the genetic alterations of long non‐coding RNAs (lncRNAs) in cancer. Thus, there is a need for systematic surveys of driver lncRNAs. Through integrative analysis of 5918 tumors across 11 cancer types, we revealed that lncRNAs have undergone dramatic genomic alterations, many of which are mutually exclusive with well‐known cancer genes. Using the hypothesis of functional redundancy of mutual exclusivity, we developed a computational framework to identify driver lncRNAs associated with different cancer hallmarks. Applying it to pan‐cancer data, we identified 378 candidate driver lncRNAs whose genomic features highly resemble the known cancer driver genes (e.g. high conservation and early replication). We further validated the candidate driver lncRNAs involved in ‘Tissue Invasion and Metastasis’ in lung adenocarcinoma and breast cancer, and also highlighted their potential roles in improving clinical outcomes. In summary, we have generated a comprehensive landscape of cancer candidate driver lncRNAs that could act as a starting point for future functional explorations, as well as the identification of biomarkers and lncRNA‐based target therapy.