Copy number changes at 8p11-12 predict adverse clinical outcome and chemo- and radiotherapy response in breast cancer

Overexpression of DUSP26 gene suppressed the proliferation, migration, and invasion of human prostate cancer cells

Prostate cancer (PCa) is threatening the health of millions of people, the pathological mechanism of prostate cancer has not been fully elaborated, and needs to be further explored. Here, we found that the expression of DUSP26 is dramatically suppressed, and a positive connection of its expression with PCa prognosis was also observed. In vitro, overexpression of DUSP26 significantly inhibited the proliferative, migrative, and invasive capacities of PC3 cells, DUSP26 silencing presented opposite results. Tumor formation experiments in subcutaneous nude mice demonstrated that DUSP26 overexpression could significantly suppress PC3 growth in vivo. Moreover, the mechanism of DUSP26 gene and PCa was discovered by RNA-Seq analysis. We found that DUSP26 significantly inhibited MAPK signaling pathway activation, and further experiments displayed that DUSP26 could impair TAK1, p38, and JNK phosphorylation. Interestingly, treatment with the TAK1 inhibitor (iTAK1) attenuated the effect of DUSP26 on PC3 cells. Together, these results suggested that DUSP26 may serve as a novel therapeutic target for PC3 cell type PCa, the underlying mechanism may be through TAK1-JNK/p38 signaling.

Characterization of Expression-Based Gene Clusters Gives Insights into Variation in Patient Response to Cancer Therapies

Background

Transcriptomics can reveal much about cellular activity, and cancer transcriptomics have been useful in investigating tumor cell behaviors. Patterns in transcriptome-wide gene expression can be used to investigate biological mechanisms and pathways that can explain the variability in patient response to cancer therapies.

Methods

We identified gene expression patterns related to patient drug response by clustering tumor gene expression data and selecting from the resulting gene clusters those where expression of cluster genes was related to patient survival on specific drugs. We then investigated these gene clusters for biological meaning using several approaches, including identifying common genomic locations and transcription factors whose targets were enriched in these clusters and performing survival analyses to support these candidate transcription factor-drug relationships.

Results

We identified gene clusters related to drug-specific survival, and through these, we were able to associate observed variations in patient drug response to specific known biological phenomena. Specifically, our analysis implicated 2 stem cell-related transcription factors, HOXB4 and SALL4, in poor response to temozolomide in brain cancers. In addition, expression of SNRNP70 and its targets were implicated in cetuximab response by 3 different analyses, although the mechanism remains unclear. We also found evidence that 2 cancer-related chromosomal structural changes may impact drug efficacy.

Conclusion

In this study, we present the gene clusters identified and the results of our systematic analysis linking drug efficacy to specific transcription factors, which are rich sources of potential mechanistic relationships impacting patient outcomes. We also highlight the most promising of these results, which were supported by multiple analyses and by previous research. We report these findings as promising avenues for independent validation and further research into cancer treatments and patient response.

Large-scale meta-genome-wide association study reveals common genetic factors linked to radiation-induced acute toxicities across cancer types

BACKGROUND

This study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).

METHODS

A genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.

RESULTS

Shared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).

CONCLUSIONS

There is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

Insights into the pleiotropic roles of ZNF703 in cancer

Zinc finger proteins (ZNFs) belong to the NET/NLZ protein family. In physiological functions, ZNF703 play significant roles in embryonic development, especially in the nervous system. As an transcription factors with zinc finger domains, abnormal regulation of the ZNF703 protein is associated with enhanced proliferation, invasion, and metastasis as well as drug resistance in many tumors, although mechanisms of action vary depending on the specific tumor microenvironment. ZNF703 lacks a nuclear localization sequence despite its function requiring nuclear DNA binding. The purpose of this review is to summarize the architecture of ZNF703, its roles in tumorigenesis, and tumor progression, as well as future oncology therapeutic prospects, which have implications for understanding tumor susceptibility and progression.

Genomic copy number alterations as biomarkers for triple negative pregnancy-associated breast cancer

Background

PABC, commonly defined as breast cancer diagnosed during or ≤ 1 year after pregnancy, accounts for 7% of all breast cancers in women ≤ 45 years. Compared to age-matched non-PABC patients, PABC is characterized by a particularly aggressive histopathologic profile with poorly differentiated and estrogen- and progesterone receptor negative tumors and associated high mortality rates. This study assessed the genomic background of triple-negative PABC tumors by detection of copy number alterations (CNAs).

Methods

MLPA was used to compare CNAs in breast cancer-associated chromosomal loci between triple-negative PABC- and subtype-matched non-PABC patients. Both CNA patterns were evaluated by cluster analysis; associations between individual gene CNAs, pathological characteristics and survival were explored.

Results

Triple-negative PABC tumors exhibited unique CNAs compared to non-PABC tumors, including enrichment for TOP2A copy number loss, an independent predictor of worse overall survival (HR 8.96, p = 0.020). Cluster analysis based on CNA profiles identified a triple-negative PABC-subgroup with a particularly poor prognosis, characterized by chromosome 8p copy number loss. Individual gene CNAs analysis revealed that FGFR1 copy number loss on chromosome 8p11.23 was an independent predictor of poor outcome in multivariate analysis (HR 3.59, p = 0.053) and predicted the development of distant metastases (p = 0.048).

Conclusion

This study provides novel insights into the biology of triple-negative PABC tumors suggesting that CNAs, particularly 8p loss and TOP2A loss, are involved in the development of breast cancer during pregnancy. FGFR1 loss and TOP2A loss seem to be promising new biomarkers that independently identify subgroups of PABC patients with poor prognosis. These genomic biomarkers may provide clues for personalized therapy.

Circulating tumor DNA is readily detectable among Ghanaian breast cancer patients supporting non-invasive cancer genomic studies in Africa

Circulating tumor DNA (ctDNA) sequencing studies could provide novel insights into the molecular pathology of cancer in sub-Saharan Africa. In 15 patient plasma samples collected at the time of diagnosis as part of the Ghana Breast Health Study and unselected for tumor grade and subtype, ctDNA was detected in a majority of patients based on whole- genome sequencing at high (30×) and low (0.1×) depths. Breast cancer driver copy number alterations were observed in the majority of patients.

Inhibition of FGF-FGFR and VEGF-VEGFR signalling in cancer treatment

The sites of targeted therapy are limited and need to be expanded. The FGF‐FGFR signalling plays pivotal roles in the oncogenic process, and FGF/FGFR inhibitors are a promising method to treat FGFR‐altered tumours. The VEGF‐VEGFR signalling is the most crucial pathway to induce angiogenesis, and inhibiting this cascade has already got success in treating tumours. While both their efficacy and antitumour spectrum are limited, combining FGF/FGFR inhibitors with VEGF/VEGFR inhibitors are an excellent way to optimize the curative effect and expand the antitumour range because their combination can target both tumour cells and the tumour microenvironment. In addition, biomarkers need to be developed to predict the efficacy, and combination with immune checkpoint inhibitors is a promising direction in the future. The article will discuss the FGF‐FGFR signalling pathway, the VEGF‐VEGFR signalling pathway, the rationale of combining these two signalling pathways and recent small‐molecule FGFR/VEGFR inhibitors based on clinical trials.

A Review of DUSP26: Structure, Regulation and Relevance in Human Disease

Dual specificity phosphatases (DUSPs) play a crucial role in the regulation of intracellular signalling pathways, which in turn influence a broad range of physiological processes. DUSP malfunction is increasingly observed in a broad range of human diseases due to deregulation of key pathways, most notably the MAP kinase (MAPK) cascades. Dual specificity phosphatase 26 (DUSP26) is an atypical DUSP with a range of physiological substrates including the MAPKs. The residues that govern DUSP26 substrate specificity are yet to be determined; however, recent evidence suggests that interactions with a binding partner may be required for DUSP26 catalytic activity. DUSP26 is heavily implicated in cancer where, akin to other DUSPs, it displays both tumour-suppressive and -promoting properties, depending on the context. Here we review DUSP26 by evaluating its transcriptional patterns, protein crystallographic structure and substrate binding, as well as its physiological role(s) and binding partners, its role in human disease and the development of DUSP26 inhibitors.

A multiple genomic data fused SF2 prediction model, signature identification, and gene regulatory network inference for personalized radiotherapy

Radiotherapy is one of the most important cancer treatments, but its response varies greatly among individual patients. Therefore, the prediction of radiosensitivity, identification of potential signature genes, and inference of their regulatory networks are important for clinical and oncological reasons. Here, we proposed a novel multiple genomic fused partial least squares deep regression method to simultaneously analyze multi-genomic data. Using 60 National Cancer Institute cell lines as examples, we aimed to identify signature genes by optimizing the radiosensitivity prediction model and uncovering regulatory relationships. A total of 113 signature genes were selected from more than 20,000 genes. The root mean square error of the model was only 0.0025, which was much lower than previously published results, suggesting that our method can predict radiosensitivity with the highest accuracy. Additionally, our regulatory network analysis identified 24 highly important ‘hub’ genes. The data analysis workflow we propose provides a unified and computational framework to harness the full potential of large-scale integrated cancer genomic data for integrative signature discovery. Furthermore, the regression model, signature genes, and their regulatory network should provide a reliable quantitative reference for optimizing personalized treatment options, and may aid our understanding of cancer progress mechanisms.

Genome-wide chromosomal instability by cell-free DNA sequencing predicts survival in patients with metastatic breast cancer

Background

Genome-wide chromosomal instability, instead of specific somatic mutations or copy-number alterations in selected genes, is a significant property of cancer and may suggest a new strategy for treatment. Here we utilized cell-free DNA (cfDNA) sequencing to display the whole picture of chromosomal instability in patients with metastatic breast cancer (MBC), and evaluate its predictive value for patient survival.

Methods

The clinical data of 65 patients who had frozen plasma and planned to change the therapeutic regimen were retrospectively enrolled. Low-coverage whole-genome sequencing of cfDNA was performed to generate the chromosomal instability represented by chromosomal instability (CIN) score.

Results

Tumors with diverse status of hormone receptor and HER2 represented diverse chromosomal instability across the whole genome. According to the receiver operating characteristic curve and the statistical distribution, CIN score exceed 3881 was defined as “High”. 32 (53.3%) patients with high CIN score had similar clinicopathologic characteristics compared with low CIN score patients. The median overall survival of patients with high CIN score was 21.2 months (95% CI 14.1–28.3), which was significantly inferior to those with low CIN score (not reached, P = 0.006). Regardless of various treatment regimens, the median progression free survival in patients with high CIN score was 7.3 months, which was significantly worse than those in the low CIN score population (11.0 months, P = 0.034). Multivariate analysis revealed that CIN score was an independent prognostic factor, with hazard ratio of 3.563 (P = 0.005).

Conclusions

To our knowledge, this is the first study illustrating the prognostic value of chromosomal instability derived from cfDNA in MBC.

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Novel UCAD pipeline to profile genome-wide chromosomal instability in cfDNA.

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Genome-wide chromosomal instability is a robust independent prognostic biomarker.

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HER2 amplification was successfully identified from cfDNA in our cohort.

Analysis of Copy-Number Variations and Feline Mammary Carcinoma Survival

Feline mammary carcinomas (FMCs) are highly malignant. As the disease-free survival (DFS) and overall survival (OS) are short, prognostication is crucial. Copy-number variations (CNVs) analysis by next-generation sequencing serves to identify critical cancer-related genomic regions. Thirty-three female cats with FMCs were followed during two years after surgery. Tumours represented tubulopapillary and solid carcinomas encompassing six molecular subtypes. Regardless of the histopathological diagnosis, molecular subtypes showed important differences in survival. Luminal A tumours exhibited the highest DFS (p = 0.002) and cancer-specific OS (p = 0.001), and the lowest amount of CNVs (p = 0.0001). In contrast, basal-like triple-negative FMCs had the worst outcome (DFS, p < 0.0001; and OS, p < 0.00001) and were the most aberrant (p = 0.05). In the multivariate analysis, copy-number losses (CNLs) in chromosome B1 (1-23 Mb) harbouring several tumour-repressors (e.g. CSMD1, MTUS1, MSR1, DBC2, and TUSC3) negatively influenced DFS. Whereas, copy-number gains (CNGs) in B4 (1-29 Mb) and F2 (64-82.3 Mb) comprising epithelial to mesenchymal transition genes and metastasis-promoting transcription factors (e.g. GATA3, VIM, ZEB1, and MYC) negatively influenced DFS and cancer-specific OS. These data evidence an association between specific CNVs in chromosomes B1, B4 and F2, and poor prognosis in FMCs.

Glutathione reductase (GSR) gene deletion and chromosome 8 aneuploidy in primary lung cancers detected by fluorescence in situ hybridization

Our recent study demonstrated that cancer cells with compromised glutathione homeostasis, including reduced expression of the glutathione reductase (GSR) gene, were selectively killed by inhibition of thioredoxin reductase. The human GSR gene is located on chromosome 8p, a region often lost in lung and other cancers. However, whether GSR is altered in primary lung cancer remains unknown. To analyze alterations of GSR in lung cancer, we performed fluorescence in situ hybridization with probes for GSR and the chromosome 8 centromere (CEP8) in 45 surgical specimens of primary lung cancer, including 24 lung adenocarcinomas, 10 squamous cell carcinomas, 8 neuroendocrine cancers, and 3 small cell lung cancers. Twenty-five surgically resected normal lung tissue specimens from these lung cancer patients were used as a controls. The signal ratio of GSR to CEP8 per cell was used to identify gain or loss of GSR. GSR loss was detected in 6 of 24 (25%) adenocarcinoma specimens and 5 of 10 (50%) squamous cell carcinoma specimens, but not in neuroendocrine cancer or small cell lung cancer specimens. We also found that 19 of 45 (42%) specimens had chromosome 8 aneuploidy (more or less than 2 signals for CEP8), including 8 with both aneuploidy and GSR deletion. Chromosome 8 aneuploidy was detected in all types of lung cancer analyzed. Univariate and multivariable logistic regression analyses indicated that male patients had an increased risk of GSR deletion (hazard ratio [HR] = 4.77, 95% confidence interval [CI] = 1.00-22.86, P = 0.051), and patients who had undergone preoperative radiation therapy or had a self-reported history of cigarette smoking had an increased risk of chromosome 8 aneuploidy (preoperative radiation: HR = 18.63, 95% CI = 0.90-384.17, P = 0.058; smoking: HR = 7.59, 95% CI = 0.86-66.75, P = 0.068), although the p values did not reach significance. Because GSR deficiency and chromosome 8 aneuploidy have implications in targeted therapy and/or immunotherapy for cancer, they might serve as predictive biomarkers for precision therapy of lung cancers.