BMC Cancer

Journal: BMC Cancer

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BMC cancer (Online)

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BioMed Central

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1471-2407

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Publications 1 - 10 of 14

A comprehensive look at transcription factor gene expression changes in colorectal adenomas
Vonlanthen, Janine; Okoniewski, Michal J.; Menigatti, Mirco; et al. (2014)
BMC Cancer
Background Biological processes are controlled by transcription networks. Expression changes of transcription factor (TF) genes in precancerous lesions are therefore crucial events in tumorigenesis. Our aim was to obtain a comprehensive picture of these changes in colorectal adenomas. Methods Using a 3-pronged selection procedure, we analyzed transcriptomic data on 34 human tissue samples (17 adenomas and paired samples of normal mucosa, all collected with ethics committee approval and written, informed patient consent) to identify TFs with highly significant tumor-associated gene expression changes whose potential roles in colorectal tumorigenesis have been under-researched. Microarray data were subjected to stringent statistical analysis of TF expression in tumor vs. normal tissues, MetaCore-mediated identification of TF networks displaying enrichment for genes that were differentially expressed in tumors, and a novel quantitative analysis of the publications examining the TF genes’ roles in colorectal tumorigenesis. Results The 261 TF genes identified with this procedure included DACH1, which plays essential roles in the proper proliferation and differentiation of retinal and leg precursor cell populations in Drosophila melanogaster. Its possible roles in colorectal tumorigenesis are completely unknown, but it was found to be markedly overexpressed (mRNA and protein) in all colorectal adenomas and in most colorectal carcinomas. However, DACH1 expression was absent in some carcinomas, most of which were DNA mismatch-repair deficient. When networks were built using the set of TF genes identified by all three selection procedures, as well as the entire set of transcriptomic changes in adenomas, five hub genes (TGFB1, BIRC5, MYB, NR3C1, and TERT) where identified as putatively crucial components of the adenomatous transformation process. Conclusion The transcription-regulating network of colorectal adenomas (compared with that of normal colorectal mucosa) is characterized by significantly altered expression of over 250 TF genes, many of which have never been investigated in relation to colorectal tumorigenesis.
Case-control Indian buffet process identifies biomarkers of response to Codrituzumab
Pradier, Melanie F.; Reis, Bernhard; Jukofsky, Lori; et al. (2019)
BMC Cancer
Background Codrituzumab, a humanized monoclonal antibody against Glypican-3 (GPC3), which is expressed in hepatocellular carcinoma (HCC), was tested in a randomized phase II trial in advanced HCC patients who had failed prior systemic therapy. Biomarker analysis was performed to identify a responder population that benefits from treatment. Methods A novel statistical method based on the Indian buffet process (IBP) was used to identify biomarkers predictive of response to treatment with Codrituzumab. The IBP is a novel method that allows flexibility in analysis design, and which is sensitive to slight, but meaningful between-group differences in biomarkers in very complex datasets Results The IBP model identified several subpopulations of patients having defined biomarker values. Tumor necrosis and viable cell content in the tumor were identified as prognostic markers of disease progression, as were the well-known HCC prognostic markers of disease progression, alpha-fetoprotein and Glypican-3 expression. Predictive markers of treatment response included natural killer (NK) cell surface markers and parameters influencing NK cell activity, all related to the mechanism of action of this drug Conclusions The Indian buffet process can be effectively used to detect statistically significant signals with high sensitivity in complex and noisy biological data
Combination of lutetium-177 labelled anti-L1CAM antibody chCE7 with the clinically relevant protein kinase inhibitor MK1775: a novel combination against human ovarian carcinoma
Lindenblatt, Dennis; Terraneo, Nastassja; Pellegrini, Giovanni; et al. (2018)
BMC Cancer
Background Protein kinase inhibitors (PKIs) are currently tested in clinical studies (phase I-III) as an alternative strategy against (recurrent) ovarian cancer. Besides their anti-tumour efficacy, several PKIs have also shown radiosensitizing effects when combined with external beam radiation. Based on these results we asked if the addition of PKIs offers a therapeutic opportunity to improve radioimmunotherapy (RIT) against ovarian cancer. Five PKIs (alisertib, MK1775, MK2206, saracatinib, temsirolimus) were chosen for cytotoxicity screenings based on their current clinical trials in the treatment of ovarian cancer and their influence on cell cycle regulation and DNA damage repair pathways. We combined selected PKIs with 177Lu-labelled anti-L1CAM monoclonal antibody chCE7 for our investigations. Methods PKIs cytotoxicity was determined via cell colony-forming assays. Biomarker of DNA double-strand breaks (DSBs, γH2A.X) was analysed by western blot and fluorescence microscopy. Flow cytometric measurements were performed to evaluate levels of apoptosis based on mono- or combination treatments. The best combination was used for in vivo combination therapy studies in nude mice with SKOV3ip and IGROV1 human ovarian cancer xenografts. Bonferroni correction was used to determine statistical significance for multiple comparisons. Results The highest cytotoxicity against both cell lines was observed for MK1775 and alisertib. Combinations including 177Lu-labelled mAb chCE7 and MK1775 decreased 177Lu-DOTA-chCE7 IC60-values 14-fold, compared to 6-fold, when the radioimmunoconjugate was combined with alisertib. The most effective PKI MK1775 was further evaluated and demonstrated synergistic effects in combination with 177Lu-DOTA-chCE7 against IGROV1 cells. Significantly higher amounts of DSBs were detected in IGROV1 cells after combination (91%) compared to either treatment alone (MK1775: 52%; radioimmunoconjugate: 72%; p < 0.0125). Early-apoptosis was significantly enhanced in IGROV1 cells correlating with induced DSBs (177Lu-DOTA-chCE7: 8%, MK1775: 28%, 177Lu-DOTA-chCE7 + MK1775: 40%, p < 0.0125). Immunohistochemistry analysis of γH2A.X expression levels after therapy in SKOV3ip xenografts revealed a high sensitivity of the tumour cells to MK1775 and a high radioresistance. A prominent effect of tumour growth inhibition of the RIT and of the combination therapy was observed in vivo in a late stage IGROV1 xenograft model. Conclusions Our results warrant further evaluation of combination of MK1775 and radioimmunotherapy.
Molecular pathways undergoing dramatic transcriptomic changes during tumor development in the human colon
Maglietta, Rosalia; Liuzzi, Vania Cosma; Cattaneo, Elisa; et al. (2012)
BMC Cancer
Background The malignant transformation of precancerous colorectal lesions involves progressive alterations at both the molecular and morphologic levels, the latter consisting of increases in size and in the degree of cellular atypia. Analyzing preinvasive tumors of different sizes can therefore shed light on the sequence of these alterations. Methods We used a molecular pathway-based approach to analyze transcriptomic profiles of 59 colorectal tumors representing early and late preinvasive stages and the invasive stage of tumorigenesis. Random set analysis was used to identify biological pathways enriched for genes differentially regulated in tumors (compared with 59 samples of normal mucosa). Results Of the 880 canonical pathways we investigated, 112 displayed significant tumor-related upregulation or downregulation at one or more stages of tumorigenesis. This allowed us to distinguish between pathways whose dysregulation is probably necessary throughout tumorigenesis and those whose involvement specifically drives progression from one stage to the next. We were also able to pinpoint specific changes within each gene set that seem to play key roles at each transition. The early preinvasive stage was characterized by cell-cycle checkpoint activation triggered by DNA replication stress and dramatic downregulation of basic transmembrane signaling processes that maintain epithelial/stromal homeostasis in the normal mucosa. In late preinvasive lesions, there was also downregulation of signal transduction pathways (e.g., those mediated by G proteins and nuclear hormone receptors) involved in cell differentiation and upregulation of pathways governing nuclear envelope dynamics and the G2>M transition in the cell cycle. The main features of the invasive stage were activation of the G1>S transition in the cell cycle, upregulated expression of tumor-promoting microenvironmental factors, and profound dysregulation of metabolic pathways (e.g., increased aerobic glycolysis, downregulation of pathways that metabolize drugs and xenobiotics). Conclusions Our analysis revealed specific pathways whose dysregulation might play a role in each transition of the transformation process. This is the first study in which such an approach has been used to gain further insights into colorectal tumorigenesis. Therefore, these data provide a launchpad for further exploration of the molecular characterization of colorectal tumorigenesis using systems biology approaches.
Prognostic relevance of Wnt-inhibitory factor-1 (WIF1) and Dickkopf-3 (DKK3) promoter methylation in human breast cancer
Veeck, Jürgen; Wild, Peter J.; Fuchs, Thomas; et al. (2009)
BMC Cancer
Background Secreted Wnt signaling antagonists have recently been described as frequent targets of epigenetic inactivation in human tumor entities. Since gene silencing of certain Wnt antagonists was found to be correlated with adverse patient survival in cancer, we aimed at investigating a potential prognostic impact of the two Wnt antagonizing molecules WIF1 and DKK3 in breast cancer, which are frequently silenced by promoter methylation in this disease. Methods WIF1 and DKK3 promoter methylation were assessed by methylation-specific PCR with bisulfite-converted DNA from 19 normal breast tissues and 150 primary breast carcinomas. Promoter methylation was interpreted in a qualitative, binary fashion. Statistical evaluations included two-sided Fisher's exact tests, univariate log-rank tests of Kaplan-Meier curves as well as multivariate Cox regression analyses. Results WIF1 and DKK3 promoter methylation were detected in 63.3% (95/150) and 61.3% (92/150) of breast carcinoma samples, respectively. In normal breast tissues, WIF1 methylation was present in 0% (0/19) and DKK3 methylation in 5.3% (1/19) of samples. In breast carcinomas, WIF1 methylation was significantly associated with methylation of DKK3 (p = 0.009). Methylation of either gene was not associated with clinicopathological parameters, except for DKK3 methylation being associated with patient age (p = 0.007). In univariate analysis, WIF1 methylation was not associated with clinical patient outcome. In contrast, DKK3 methylation was a prognostic factor in patient overall survival (OS) and disease-free survival (DFS). Estimated OS rates after 10 years were 54% for patients with DKK3-methylated tumors, in contrast to patients without DKK3 methylation in the tumor, who had a favorable 97% OS after 10 years (p < 0.001). Likewise, DFS at 10 years for patients harboring DKK3 methylation in the tumor was 58%, compared with 78% for patients with unmethylated DKK3 (p = 0.037). Multivariate analyses revealed that DKK3 methylation was an independent prognostic factor predicting poor OS (hazard ratio (HR): 14.4; 95% confidence interval (CI): 1.9–111.6; p = 0.011), and short DFS (HR: 2.5; 95% CI: 1.0–6.0; p = 0.047) in breast cancer. Conclusion Although the Wnt antagonist genes WIF1 and DKK3 show a very similar frequency of promoter methylation in human breast cancer, only DKK3 methylation proves as a novel prognostic marker potentially useful in the clinical management of this disease.
Exploring RNA cargo in extracellular vesicles for pleural mesothelioma detection
Kraft, Agnieszka; Kirschner, Michaela B.; Orlowski, Vanessa; et al. (2025)
BMC Cancer
Background Pleural Mesothelioma (PM) is a highly aggressive cancer, for which effective early detection remains a challenge due to limited screening options and low sensitivity of biomarkers discovered so far. While extracellular vesicles (EVs) have emerged as promising candidates for blood-based biomarkers, their role in PM has not been studied yet. In this study, we characterized the transcriptomic profile of EVs secreted by PM primary cells and explored their potential as a biomarker source for PM detection. Methods We collected cell culture supernatant from early-passage PM cell cultures derived from the pleural effusion of 4 PM patients. EVs were isolated from the supernatant using Qiagen exoEasy Maxi kit. RNA isolation from EVs was done using the mirVana PARIS kit. Finally, single-end RNA sequencing was done with Illumina Novaseq 6000. Results We identified a range of RNA species expressed in EVs secreted by PM cells, including protein-coding RNA (80%), long non-coding RNA (13%), pseudogenes (4.5%), and short non-coding RNA (1.6%). We detected a subset of genes associated with the previously identified epithelioid (32 genes) and sarcomatoid molecular components (36 genes) in PM-EVs. To investigate whether these markers could serve as biomarkers for PM detection in blood, we compared the RNA content of PM-EVs with the cargo of EVs isolated from the plasma of healthy donors (publicly available data). Majority of upregulated genes in PM-EVs were protein-coding and long non-coding RNAs. Interestingly, 25 of them were the sarcomatoid and epithelioid marker genes. Finally, functional analysis revealed that the PM-EV RNA cargo was associated with Epithelial-Mesenchymal transition, glycolysis, and hypoxia. Conclusions This is the first study to characterize the transcriptomic profile of EVs secreted by PM primary cell cultures, demonstrating their potential as biomarker source for early detection. Further investigation of the functional role of PM-EVs will provide new insights into disease biology and therapeutic avenues.
Validation of hypermethylated DNA regions found in colorectal cancers as potential aging-independent biomarkers of precancerous colorectal lesions
Sajibu, Sija; Sonder, Emanuel; Tiwari, Amit; et al. (2023)
BMC Cancer
Background: We previously identified 16,772 colorectal cancer-associated hypermethylated DNA regions that were also detectable in precancerous colorectal lesions (preCRCs) and unrelated to normal mucosal aging. We have now conducted a study to validate 990 of these differentially methylated DNA regions (DMRs) in a new series of preCRCs. Methods: We used targeted bisulfite sequencing to validate these 990 potential biomarkers in 59 preCRC tissue samples (41 conventional adenomas, 18 sessile serrated lesions), each with a patient-matched normal mucosal sample. Based on differential DNA methylation tests, a panel of candidate DMRs was chosen on a subset of our cohort and then validated on the remaining part of our cohort and two publicly available datasets with respect to their stratifying potential between preCRCs and normal mucosa. Results: Strong statistical significance for the difference in methylation levels was observed across the full set of 990 investigated DMRs. From these, a selected candidate panel of 30 DMRs correctly identified 58/59 tumors (area under the receiver operating curve: 0.998). Conclusions: These validated DNA hypermethylation markers can be exploited to develop more accurate noninvasive colorectal tumor screening assays.
Nuclear detection of Y-boxprotein-1 (YB-1) closely associates with progesterone receptor negativity and is a strong adverse survival factor in human breast cancer
Dahl, Edgar; En-Nia, Abdelaziz; Wiesmann, Frank; et al. (2009)
BMC Cancer
Background Y-box binding protein-1 (YB-1) is the prototypic member of the cold shock protein family that fulfills numerous cellular functions. In the nucleus YB-1 protein orchestrates transcription of proliferation-related genes, whereas in the cytoplasm it associates with mRNA and directs translation. In human tumor entities, such as breast, lung and prostate cancer, cellular YB-1 expression indicates poor clinical outcome, suggesting that YB-1 is an attractive marker to predict patients' prognosis and, potentially, is suitable to individualize treatment protocols. Given these predictive qualities of YB-1 detection we sought to establish a highly specific monoclonal antibody (Mab) for diagnostic testing and its characterization towards outcome prediction (relapse-free and overall survival). Methods Hybridoma cell generation was carried out with recombinant YB-1 protein as immunogen and Mab characterization was performed using immunoblotting and ELISA with recombinant and tagged YB-1 proteins, as well as immunohistochemistry of healthy and breast cancer specimens. Breast tumor tissue array staining results were analyzed for correlations with receptor expression and outcome parameters. Results YB-1-specific Mab F-E2G5 associates with conformational binding epitopes mapping to two domains within the N-terminal half of the protein and detects nuclear YB-1 protein by immunohistochemistry in paraffin-embedded breast cancer tissues. Prognostic evaluation of Mab F-E2G5 was performed by immunohistochemistry of a human breast cancer tissue microarray comprising 179 invasive breast cancers, 8 ductal carcinoma in situ and 37 normal breast tissue samples. Nuclear YB-1 detection in human breast cancer cells was associated with poor overall survival (p = 0.0046). We observed a close correlation between nuclear YB-1 detection and absence of progesterone receptor expression (p = 0.002), indicating that nuclear YB-1 detection marks a specific subgroup of breast cancer. Likely due to limitation of sample size Cox regression models failed to demonstrate significance for nuclear YB-1 detection as independent prognostic marker. Conclusion Monoclonal YB-1 antibody F-E2G5 should be of great value for prospective studies to validate YB-1 as a novel biomarker suitable to optimize breast cancer treatment.
Physical activity interventions to improve daily walking activity in cancer survivors
Knols, Ruud H.; de Bruin, Eling; Shirato, Kei; et al. (2010)
BMC Cancer
Background Cancer patients may benefit from physical exercise programs. It is unclear, however, how sustained levels of physical activity are best achieved in this population. A systematic review was performed to summarize the current evidence of the effect of physical activity interventions on daily walking activity enhancement in cancer survivors, and to review the literature for its methodological quality. Methods A search in Medline, PEDro and the Cochrane databases was performed for English literature citations (randomized controlled trials; 'RCTs'). In a first step, one reviewer abstracted data from the included studies on patients, physical activity interventions and outcomes. Two independent reviewers reviewed the methodological quality of these studies. Data were pooled using random-effects calculations. Results Our search identified 201 citations. Five RCTs that reported changes in daily step activity over time were identified, and were reviewed for methodological quality and substantive results. The median score across studies for methodological quality based on the PEDro criteria was 8. These 5 RCTs evaluated 660 participants with a mean age of 53.6 (SD 4.2) years. The mean change in daily step activity for patients with a physical exercise intervention was 526 daily steps (SD 537), with a range from -92 to 1299 daily steps. The data of three studies reporting the effect of combined physical activity and counseling on daily walking activity in breast cancer survivors were pooled, however; the I2 was 79%, indicating statistical heterogeneity between the three trials. Conclusion The 5 RCTs reviewed were of good methodological quality. Together they suggest that combined physical activity and counseling improves daily step activity in (breast) cancer survivors. Studies that define a step goal appear to be more effective in improving daily walking activity than studies that do not do so. However, the current results should be interpreted with caution because of the observed clinical and statistical heterogeneity. Future studies are warranted to evaluate the effects of goal targeted physical activity, with or without counseling, on daily walking in various cancer populations.
Realizing the promise of machine learning in precision oncology: expert perspectives on opportunities and challenges
Nittas, Vasileios; Ormond, Kelly; Vayena, Effy; et al. (2025)
BMC Cancer
BackgroundThe ability of machine learning (ML) to process and learn from large quantities of heterogeneous patient data is gaining attention in the precision oncology community. Some remarkable developments have taken place in the domain of image classification tasks in areas such as digital pathology and diagnostic radiology. The application of ML approaches to the analysis of DNA data, including tumor-derived genomic profiles, microRNAs, and cancer epigenetic signatures, while relatively more recent, has demonstrated some utility in identifying driver variants and molecular signatures with possible prognostic and therapeutic applications.MethodsWe conducted semi-structured interviews with academic and clinical experts to capture the status quo, challenges, opportunities, ethical implications, and future directions.ResultsOur participants agreed that machine learning in precision oncology is in infant stages, with clinical integration still rare. Overall, participants equated ongoing developments with better clinical workflows and improved treatment decisions for more cancer patients. They underscored the ability of machine learning to tackle the dynamic nature of cancer, break down the complexity of molecular data, and support decision-making. Our participants emphasized obstacles related to molecular data access, clinical utility, and guidelines. The availability of reliable and well-curated data to train and validate machine learning algorithms and integrate multiple data sources were described as constraints yet necessary for future clinical implementation. Frequently mentioned ethical challenges included privacy risks, equity, explainability, trust, and incidental findings, with privacy being the most polarizing. While participants recognized the issue of hype surrounding machine learning in precision oncology, they agreed that, in an assistive role, it represents the future of precision oncology.ConclusionsGiven the unique nature of medical AI, our findings highlight the field's potential and remaining challenges. ML will continue to advance cancer research and provide opportunities for patient-centric, personalized, and efficient precision oncology. Yet, the field must move beyond hype and toward concrete efforts to overcome key obstacles, such as ensuring access to molecular data, establishing clinical utility, developing guidelines and regulations, and meaningfully addressing ethical challenges.

Publications 1 - 10 of 14

Journal: BMC Cancer

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