Network-based analysis of prostate cancer cell lines reveals novel marker gene candidates associated with radioresistance and patient relapse

Network-based analysis of heterogeneous patient-matched brain and extracranial melanoma metastasis pairs reveals three homogeneous subgroups

Melanoma, the deadliest form of skin cancer, can metastasize to different organs. Molecular differences between brain and extracranial melanoma metastases are poorly understood. Here, promoter methylation and gene expression of 11 heterogeneous patient-matched pairs of brain and extracranial metastases were analyzed using melanoma-specific gene regulatory networks learned from public transcriptome and methylome data followed by network-based impact propagation of patient-specific alterations. This innovative data analysis strategy allowed to predict potential impacts of patient-specific driver candidate genes on other genes and pathways. The patient-matched metastasis pairs clustered into three robust subgroups with specific downstream targets with known roles in cancer, including melanoma (SG1: RBM38, BCL11B, SG2: GATA3, FES, SG3: SLAMF6, PYCARD). Patient subgroups and ranking of target gene candidates were confirmed in a validation cohort. Summarizing, computational network-based impact analyses of heterogeneous metastasis pairs predicted individual regulatory differences in melanoma brain metastases, cumulating into three consistent subgroups with specific downstream target genes.

Personalized identification and characterization of genome-wide gene expression differences between patient-matched intracranial and extracranial melanoma metastasis pairs

Melanoma is the most serious type of skin cancer that frequently spreads to other organs of the human body. Especially melanoma metastases to the brain (intracranial metastases) are hard to treat and a major cause of death of melanoma patients. Little is known about molecular alterations and altered mechanisms that distinguish intra- from extracranial melanoma metastases. So far, almost all existing studies compared intracranial metastases from one set of patients to extracranial metastases of an another set of melanoma patients. This neglects the important facts that each melanoma is highly individual and that intra- and extracranial melanoma metastases from the same patient are more similar to each other than to melanoma metastases from other patients in the same organ. To overcome this, we compared the gene expression profiles of 16 intracranial metastases to their corresponding 21 patient-matched extracranial metastases in a personalized way using a three-state Hidden Markov Model (HMM) to identify altered genes for each individual metastasis pair. This enabled three major findings by considering the predicted gene expression alterations across all patients: (i) most frequently altered pathways include cytokine-receptor interaction, calcium signaling, ECM-receptor interaction, cAMP signaling, Jak-STAT and PI3K/Akt signaling, (ii) immune-relevant signaling pathway genes were downregulated in intracranial metastases, and (iii) intracranial metastases were associated with a brain-like phenotype gene expression program. Further, the integration of all differentially expressed genes across the patient-matched melanoma metastasis pairs led to a set of 103 genes that were consistently down- or up-regulated in at least 11 of the 16 of the patients. This set of genes contained many genes involved in the regulation of immune responses, cell growth, cellular signaling and transport processes. An analysis of these genes in the TCGA melanoma cohort showed that the expression behavior of 11 genes was significantly associated with survival. Moreover, a comparison of the 103 genes to three closely related melanoma metastasis studies revealed a core set of eight genes that were consistently down- or upregulated in intra- compared to extracranial metastases in at least two of the three related studies (down: CILP, DPT, FGF7, LAMP3, MEOX2, TMEM119; up: GLDN, PMP2) including FGF7 that was also significantly associated with survival. Our findings contribute to a better characterization of genes and pathways that distinguish intra- from extracranial melanoma metastasis and provide important hints for future experimental studies to identify potential targets for new therapeutic approaches.

The upregulation of VGF enhances the progression of oral squamous carcinoma

BACKGROUND

Oral squamous cell carcinoma (OSCC) is a prevalent neoplasm worldwide, necessitating a deeper understanding of its pathogenesis. VGF nerve growth factor inducible (VGF), a neuropeptide, plays critical roles in nerve and endocrine cell regulation.

METHODS

In this study, the TCGA datasets were initially screened, identifying the upregulation of VGF in various malignancies. We focused on OSCC cell lines, identifying the suppressor mRNA miR-432-5p as a negative regulator of VGF. Additionally, we examined the prognostic value of VGF expression in OSCC tumors and its impact on cellular functions.

RESULTS

VGF expression was found to be an independent prognostic predictor in OSCC tumors. Cells expressing VGF exhibited increased oncogenicity, influencing the proliferation and migration of oral mucosal fibroblast. Transcriptome analysis revealed associations between VGF and various pathological processes, including malignancies, exosome release, fibrosis, cell cycle disruption, and tumor immune suppression. Moreover, IL23R expression, a favorable OSCC prognostic factor, was inversely correlated with VGF expression. Exogenous IL23R expression was found to suppress VGF-associated mobility phenotypes.

CONCLUSIONS

This study highlights the multifaceted role of VGF in OSCC pathogenesis and introduces the miR-432-5p-VGF-IL23R regulatory axis as a critical mediator. The combined expression of VGF and IL23R emerges as a potent predictor of survival in oral carcinoma cases, suggesting potential implications for future therapeutic strategies.

Senescence-associated secretory phenotype constructed detrimental and beneficial subtypes and prognostic index for prostate cancer patients undergoing radical prostatectomy

BACKGROUND

Cellular senescence is growing in popularity in cancer. A dual function is played by the senescence-associated secretory phenotype (SASP) that senescent cells produce in the development of pro-inflammatory niches, tissue regeneration or destruction, senescence propagation, and malignant transformation. In this study, we conducted thorough bioinformatic analysis and meta-analysis to discover detrimental and beneficial subtypes and prognostic index for prostate cancer (PCa) patients using the experimentally confirmed SASP genes.

METHODS

We identified differentially expressed and prognosis-related SASP genes and used them to construct two molecular subtypes and risk score. Another two external cohorts were used to confirm the prognostic effect of the above subtypes and risk score and meta-analysis was further conducted. Additionally, functional analysis, tumor stemness and heterogeneity and tumor microenvironment were also evaluated. We completed analyses using software R 3.6.3 and its suitable packages. Meta-analysis was performed by software Stata 14.0.

RESULTS

Through multivariate Cox regression analysis and consensus clustering analysis, we used VGF, IGFBP3 and ANG to establish detrimental and beneficial subtypes in the TCGA cohort, which was validated through other two independent cohorts. Meta-analysis showed that detrimental SASP group had significantly higher risk of biochemical recurrence (BCR) than beneficial SASP group (HR: 2.48). Moreover, we also constructed and validated risk score based on these genes to better guide clinical practice. DNA repair, MYC target, oxidative phosphorylation, proteasome and ribosome were highly enriched in detrimental SASP group. Detrimental SASP group had significantly higher levels of B cells, CD8+ T cells, homologous recombination deficiency, loss of heterozygosity, microsatellite instability, purity, tumor mutation burden, mRNAsi, differentially methylated probes and epigenetically regulated RNA expression than beneficial SASP group. The top mutation genes between detrimental and beneficial SASP groups were SPOP, FOXA1, KMT2C, APC, BSN, DNAH17, MYH6, EPPK1, ZNF536 and ZC3H13 with statistical significance.

CONCLUSIONS

From perspective of SASP, we found detrimental and beneficial tumor subtypes which were closely associated with BCR-free survival for PCa patients, which might be important for the furture research in the field of PCa.

SREBF2-STARD4 axis confers sorafenib resistance in hepatocellular carcinoma by regulating mitochondrial cholesterol homeostasis

Sorafenib resistance limits its survival benefit for treatment of hepatocellular carcinoma (HCC). Cholesterol metabolism is dysregulated in HCC, and its role in sorafenib resistance of HCC has not been fully elucidated. Aiming to elucidate this, in vitro and in vivo sorafenib resistant models were established. Sterol regulatory element binding transcription factor 2 (SREBF2), the key regulator of cholesterol metabolism, was activated in sorafenib resistant HepG2 and Huh7 cells. Knockdown of SREBF2 resensitized sorafenib resistant cells and xenografts tumors to sorafenib. Further study showed that SREBF2 positively correlated with StAR related lipid transfer domain containing 4 (STARD4) in our sorafenib resistant models and publicly available datasets. STARD4, mediating cholesterol trafficking, not only promoted proliferation and migration of HepG2 and Huh7 cells, but also increased sorafenib resistance in liver cancer. Mechanically, SREBF2 promoted expression of STARD4 by directly binding to its promoter region, leading to increased mitochondrial cholesterol levels and inhibition of mitochondrial cytochrome c release. Importantly, knockdown of SREBF2 or STARD4 decreased mitochondrial cholesterol levels and increased mitochondrial cytochrome c release, respectively. Moreover, overexpression of STARD4 reversed the effect of SREBF2 knockdown on mitochondrial cytochrome c release and sorafenib resistance. In conclusion, SREBF2 promotes STARD4 transcription, which in turn contributes to mitochondrial cholesterol transport and sorafenib resistance in HCC. Therefore, targeting the SREBF2-STARD4 axis would be beneficial to a subset of HCC patients with sorafenib resistance.

Radioresistance Mechanisms in Prostate Cancer Cell Lines Surviving Ultra-Hypo-Fractionated EBRT: Implications and Possible Clinical Applications

The use of a higher dose per fraction to overcome the high radioresistance of prostate cancer cells has been unsuccessfully proposed. Herein, we present PC3 and DU-145, castration-resistant prostate cancer cell lines that survived a clinically used ultra-higher dose per fraction, namely, radioresistant PC3 and DU-145 cells (PC3RR and DU-145RR). Compared to PC3, PC3RR showed a higher level of aggressive behaviour, with enhanced clonogenic potential, DNA damage repair, migration ability and cancer stem cell features. Furthermore, compared to PC3, PC3RR more efficiently survived further radiation by increasing proliferation and down-regulating pro-apoptotic proteins. No significant changes of the above parameters were described in DU-145RR, suggesting that different prostate cancer cell lines that survive ultra-higher dose per fraction do not display the same grade of aggressive phenotype. Furthermore, both PC3RR and DU-145RR increased antioxidant enzymes and mesenchymal markers. Our data suggest that different molecular mechanisms could be potential targets for future treatments plans based on sequential strategies and synergistic effects of different modalities, possibly in a patient-tailored fashion. Moreover, PC3RR cells displayed an increase in specific markers involved in bone remodeling, indicating that radiotherapy selects a PC3 population capable of migrating to secondary metastatic sites. Finally, PC3RR cells showed a better sensitivity to Docetaxel as compared to native PC3 cells. This suggests that a subset of patients with castration-resistant metastatic disease could benefit from upfront Docetaxel treatment after the failure of radiotherapy.

Computational gene expression analysis reveals distinct molecular subgroups of T-cell prolymphocytic leukemia

T-cell prolymphocytic leukemia (T-PLL) is a rare blood cancer with poor prognosis. Overexpression of the proto-oncogene TCL1A and missense mutations of the tumor suppressor ATM are putative main drivers of T-PLL development, but so far only little is known about the existence of T-PLL gene expression subtypes. We performed an in-depth computational reanalysis of 68 gene expression profiles of one of the largest currently existing T-PLL patient cohorts. Hierarchical clustering combined with bootstrapping revealed three robust T-PLL gene expression subgroups. Additional comparative analyses revealed similarities and differences of these subgroups at the level of individual genes, signaling and metabolic pathways, and associated gene regulatory networks. Differences were mainly reflected at the transcriptomic level, whereas gene copy number profiles of the three subgroups were much more similar to each other, except for few characteristic differences like duplications of parts of the chromosomes 7, 8, 14, and 22. At the network level, most of the 41 predicted potential major regulators showed subgroup-specific expression levels that differed at least in comparison to one other subgroup. Functional annotations suggest that these regulators contribute to differences between the subgroups by altering processes like immune responses, angiogenesis, cellular respiration, cell proliferation, apoptosis, or migration. Most of these regulators are known from other cancers and several of them have been reported in relation to leukemia (e.g. AHSP, CXCL8, CXCR2, ELANE, FFAR2, G0S2, GIMAP2, IL1RN, LCN2, MBTD1, PPP1R15A). The existence of the three revealed T-PLL subgroups was further validated by a classification of T-PLL patients from two other smaller cohorts. Overall, our study contributes to an improved stratification of T-PLL and the observed subgroup-specific molecular characteristics could help to develop urgently needed targeted treatment strategies.

Prostate cancer in omics era

Recent advances in omics technology have prompted extraordinary attempts to define the molecular changes underlying the onset and progression of a variety of complex human diseases, including cancer. Since the advent of sequencing technology, cancer biology has become increasingly reliant on the generation and integration of data generated at these levels. The availability of multi-omic data has transformed medicine and biology by enabling integrated systems-level approaches. Multivariate signatures are expected to play a role in cancer detection, screening, patient classification, assessment of treatment response, and biomarker identification. This review reports current findings and highlights a number of studies that are both novel and groundbreaking in their application of multi Omics to prostate cancer.

Enhancing Cancer Driver Gene Prediction by Protein-Protein Interaction Network

With the advances in gene sequencing technologies, millions of somatic mutations have been reported in the past decades, but mining cancer driver genes with oncogenic mutations from these data remains a critical and challenging area of research. In this study, we proposed a network-based classification method for identifying cancer driver genes with merging the multi-biological information. In this method, we construct a cancer specific genetic network from the human protein-protein interactome (PPI) to mine the network structure attributes, and combine biological information such as mutation frequency and differential expression of genes to achieve accurate prediction of cancer driver genes. Across seven different cancer types, the proposed algorithm always achieves high prediction accuracy, which is superior to the existing advanced methods. In the analysis of the predicted results, about 40 percent of the top 10 candidate genes overlap with the Cancer Gene Census database. Interestingly, the feature comparison indicates that the network based features are still more important than the biological features, including the mutation frequency and genetic differential expression. Further analyses also show that the integration of network structure attributes and biological information is valuable for predicting new cancer driver genes.

HOXA1, a breast cancer oncogene

More than 25 years ago, the first literature records mentioned HOXA1 expression in human breast cancer. A few years later, HOXA1 was confirmed as a proper oncogene in mammary tissue. In the following two decades, molecular data about the mode of action of the HOXA1 protein, the factors contributing to activate and maintain HOXA1 gene expression and the identity of its target genes have accumulated and provide a wider view on the association of this transcription factor to breast oncogenesis. Large-scale transcriptomic data gathered from wide cohorts of patients further allowed refining the relationship between breast cancer type and HOXA1 expression. Several recent reports have reviewed the connection between cancer hallmarks and the biology of HOX genes in general. Here we take HOXA1 as a paradigm and propose an extensive overview of the molecular data centered on this oncoprotein, from what its expression modulators, to the interactors contributing to its oncogenic activities, and to the pathways and genes it controls. The data converge to an intricate picture that answers questions on the multi-modality of its oncogene activities, point towards better understanding of breast cancer aetiology and thereby provides an appraisal for treatment opportunities.

AKR1B10 as a Potential Novel Serum Biomarker for Breast Cancer: A Pilot Study

Background

Aldo-keto reductase 1B10 (AKR1B10) is a secretory protein that is upregulated in breast cancer.

Objective

This case-controlled pilot study evaluated the serum level of AKR1B10 in healthy women and patients with a localized or metastatic breast cancer.

Methods

AKR1B10 levels were measured by ELISA and IHC in several patient cohorts.

Results

Our data showed that serum AKR1B10 was significantly elevated in patients with localized (6.72 ± 0.92 ng/ml) or metastatic (7.79 ± 1.13 ng/ml) disease compared to cancer-free healthy women (1.69 ± 0.17 ng/ml) (p<0.001); the serum AKR1B10 was correlated with its expression in tumor tissues, but not with the tumor burden, molecular subtypes or histological stages. After surgical removal of primary tumors, the serum AKR1B10 was rapidly decreased within 3 days and plateaued at a level similar to that of healthy controls in most patients. ROC curve analysis suggested the optimal diagnostic cut-off value of serum AKR1B10 at 3.456 ng/ml with AUC 0.9045 ± 0.0337 (95% CI 0.8384 - 0.9706), sensitivity 84.75% (95% CI 73.01% to 92.78%), and specificity 93.88% (95% CI 83.13% to 98.72%).

Conclusions

These data indicate the potential value of serum AKR1B10 as a biomarker of breast cancer.

Acquired resistance to irradiation or docetaxel is not associated with cross-resistance to cisplatin in prostate cancer cell lines

PURPOSE

Platinum chemotherapy can be considered to treat metastatic castration-resistant prostate cancer (mCRPC) with features of neuroendocrine differentiation. However, platinum compounds are generally only applied after the failure of multiple prior-line treatment options. This study investigated whether acquired resistance against ionizing radiation or docetaxel chemotherapy-two commonly applied treatment modalities in prostate cancer-influences the cisplatin (CDDP) tolerance in mCRPC cell line models.

METHODS

Age-matched parental as well as radio- or docetaxel-resistant DU145 and PC-3 cell lines were treated with CDDP and their sensitivity was assessed by measurements of growth rates, viability, apoptosis, metabolic activity and colony formation ability.

RESULTS

The data suggest that docetaxel resistance does not influence CDDP tolerance in all tested docetaxel-resistant cell lines. Radio-resistance was associated with sensitization to CDDP in PC-3, but not in DU145 cells. In general, DU145 cells tolerated higher CDDP concentrations than PC-3 cells regardless of acquired resistances. Furthermore, non-age-matched treatment-naïve PC-3 cells exhibited significantly different CDDP tolerances.

CONCLUSION

Like patients, different mCRPC cell lines exhibit significant variability regarding CDDP tolerance. The presented in vitro data suggest that previous radiation treatment may be associated with a moderate sensitization to CDDP in an isogenic and age-matched setting. Therefore, previous radiotherapy or docetaxel chemotherapy might be no contraindication against initiation of platinum chemotherapy in selected mCRPC patients.

Advanced Pathogenetic Concepts in T-Cell Prolymphocytic Leukemia and Their Translational Impact

T-cell prolymphocytic leukemia (T-PLL) is the most common mature T-cell leukemia. It is a typically aggressively growing and chemotherapy-resistant malignancy with a poor prognosis. T-PLL cells resemble activated, post-thymic T-lymphocytes with memory-type effector functions. Constitutive transcriptional activation of genes of the T-cell leukemia 1 (TCL1) family based on genomic inversions/translocations is recognized as a key event in T-PLL's pathogenesis. TCL1's multiple effector pathways include the enhancement of T-cell receptor (TCR) signals. New molecular dependencies around responses to DNA damage, including repair and apoptosis regulation, as well as alterations of cytokine and non-TCR activation signaling were identified as perturbed hallmark pathways within the past years. We currently witness these vulnerabilities to be interrogated in first pre-clinical concepts and initial clinical testing in relapsed/refractory T-PLL patients. We summarize here the current knowledge on the molecular understanding of T-PLL's pathobiology and critically assess the true translational progress around this to help appraisal by caregivers and patients. Overall, the contemporary concepts on T-PLL's pathobiology are condensed in a comprehensive mechanistic disease model and promising interventional strategies derived from it are highlighted.

The Multifaceted Role of Aldehyde Dehydrogenases in Prostate Cancer Stem Cells

Cancer stem cells (CSCs) are the only tumor cells possessing self-renewal and differentiation properties, making them an engine of tumor progression and a source of tumor regrowth after treatment. Conventional therapies eliminate most non-CSCs, while CSCs often remain radiation and drug resistant, leading to tumor relapse and metastases. Thus, targeting CSCs might be a powerful tool to overcome tumor resistance and increase the efficiency of current cancer treatment strategies. The identification and isolation of the CSC population based on its high aldehyde dehydrogenase activity (ALDH) is widely accepted for prostate cancer (PCa) and many other solid tumors. In PCa, several ALDH genes contribute to the ALDH activity, which can be measured in the enzymatic assay by converting 4, 4-difluoro-4-bora-3a, 4a-diaza-s-indacene (BODIPY) aminoacetaldehyde (BAAA) into the fluorescent product BODIPY-aminoacetate (BAA). Although each ALDH isoform plays an individual role in PCa biology, their mutual functional interplay also contributes to PCa progression. Thus, ALDH proteins are markers and functional regulators of CSC properties, representing an attractive target for cancer treatment. In this review, we discuss the current state of research regarding the role of individual ALDH isoforms in PCa development and progression, their possible therapeutic targeting, and provide an outlook for the future advances in this field.

Screening of genes related to survival prognosis of cervical squamous cell carcinoma and construction of prognosis prediction model

AIM

We aimed to screen for the genes related to survival prognosis of cervical squamous cell carcinoma (CSCC) and then constructed a prognosis prediction model.

METHODS

The GSE63514 dataset was obtained from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO). The CSCC gene dataset and the GSE44001 dataset were obtained from The Cancer Genome Atlas and NCBI GEO, respectively. The Kaplan-Meier (KM) curve was used to evaluate the association between high and low prognosis that was with the actual survival prognosis information. The Cox proportional hazards model was used to screen out the optimized prognostic-related signature differentially expressed gene (DEG) combinations. Gene set enrichment analysis was used to perform pathway enrichment annotation analysis for DEGs that were related to risk grouping.

RESULTS

In total, 16 399 DEGs were obtained and 23 gene ontology biological processes and 8 Kyoto Encyclopedia of Genes and Genomes pathways were screened. Nine optimized DEG groups related to independent prognosis were selected. The KM curves of pathologic N0 and N1 showed that low-risk group were associated with a better overall survival (p = 1.518e; p = 1.704e-01). The pathways related to risk grouping were cytokine-cytokine receptor interaction, JAK stat signaling pathway, and glycolysis-gluconeogenesis.

CONCLUSION

On the basis of this study, we established a prognostic risk model, which provided a reliable prognostic tool and was of great significance for locating the biomarkers related to survival prognosis in CSCC.

Integrated Analysis of the Roles of RNA Binding Proteins and Their Prognostic Value in Clear Cell Renal Cell Carcinoma

Methods

We downloaded the RNA sequencing data of ccRCC from the Cancer Genome Atlas (TCGA) database and identified differently expressed RBPs in different tissues. In this study, we used bioinformatics to analyze the expression and prognostic value of RBPs; then, we performed functional analysis and constructed a protein interaction network for them. We also screened out some RBPs related to the prognosis of ccRCC. Finally, based on the identified RBPs, we constructed a prognostic model that can predict patients' risk of illness and survival time. Also, the data in the HPA database were used for verification.

Results

In our experiment, we obtained 539 ccRCC samples and 72 normal controls. In the subsequent analysis, 87 upregulated RBPs and 38 downregulated RBPs were obtained. In addition, 9 genes related to the prognosis of patients were selected, namely, RPL36A, THOC6, RNASE2, NOVA2, TLR3, PPARGC1A, DARS, LARS2, and U2AF1L4. We further constructed a prognostic model based on these genes and plotted the ROC curve. This ROC curve performed well in judgement and evaluation. A nomogram that can judge the patient's life span is also made.

Conclusion

In conclusion, we have identified differentially expressed RBPs in ccRCC and carried out a series of in-depth research studies, the results of which may provide ideas for the diagnosis of ccRCC and the research of new targeted drugs.

GLS-driven glutamine catabolism contributes to prostate cancer radiosensitivity by regulating the redox state, stemness and ATG5-mediated autophagy

Radiotherapy is one of the curative treatment options for localized prostate cancer (PCa). The curative potential of radiotherapy is mediated by irradiation-induced oxidative stress and DNA damage in tumor cells. However, PCa radiocurability can be impeded by tumor resistance mechanisms and normal tissue toxicity. Metabolic reprogramming is one of the major hallmarks of tumor progression and therapy resistance. Specific metabolic features of PCa might serve as therapeutic targets for tumor radiosensitization and as biomarkers for identifying the patients most likely to respond to radiotherapy. The study aimed to characterize a potential role of glutaminase (GLS)-driven glutamine catabolism as a prognostic biomarker and a therapeutic target for PCa radiosensitization. Methods: We analyzed primary cell cultures and radioresistant (RR) derivatives of the conventional PCa cell lines by gene expression and metabolic assays to identify the molecular traits associated with radiation resistance. Relative radiosensitivity of the cell lines and primary cell cultures were analyzed by 2-D and 3-D clonogenic analyses. Targeting of glutamine (Gln) metabolism was achieved by Gln starvation, gene knockdown, and chemical inhibition. Activation of the DNA damage response (DDR) and autophagy was assessed by gene expression, western blotting, and fluorescence microscopy. Reactive oxygen species (ROS) and the ratio of reduced glutathione (GSH) to oxidized glutathione (GSSG) were analyzed by fluorescence and luminescence probes, respectively. Cancer stem cell (CSC) properties were investigated by sphere-forming assay, CSC marker analysis, and in vivo limiting dilution assays. Single circulating tumor cells (CTCs) isolated from the blood of PCa patients were analyzed by array comparative genome hybridization. Expression levels of the GLS1 and MYC gene in tumor tissues and amino acid concentrations in blood plasma were correlated to a progression-free survival in PCa patients. Results: Here, we found that radioresistant PCa cells and prostate CSCs have a high glutamine demand. GLS-driven catabolism of glutamine serves not only for energy production but also for the maintenance of the redox state. Consequently, glutamine depletion or inhibition of critical regulators of glutamine utilization, such as GLS and the transcription factor MYC results in PCa radiosensitization. On the contrary, we found that a combination of glutamine metabolism inhibitors with irradiation does not cause toxic effects on nonmalignant prostate cells. Glutamine catabolism contributes to the maintenance of CSCs through regulation of the alpha-ketoglutarate (α-KG)-dependent chromatin-modifying dioxygenase. The lack of glutamine results in the inhibition of CSCs with a high aldehyde dehydrogenase (ALDH) activity, decreases the frequency of the CSC populations in vivo and reduces tumor formation in xenograft mouse models. Moreover, this study shows that activation of the ATG5-mediated autophagy in response to a lack of glutamine is a tumor survival strategy to withstand radiation-mediated cell damage. In combination with autophagy inhibition, the blockade of glutamine metabolism might be a promising strategy for PCa radiosensitization. High blood levels of glutamine in PCa patients significantly correlate with a shorter prostate-specific antigen (PSA) doubling time. Furthermore, high expression of critical regulators of glutamine metabolism, GLS1 and MYC, is significantly associated with a decreased progression-free survival in PCa patients treated with radiotherapy. Conclusions: Our findings demonstrate that GLS-driven glutaminolysis is a prognostic biomarker and therapeutic target for PCa radiosensitization.

Inhibiting p21-activated kinase (PAK7) enhances radiosensitivity in hepatocellular carcinoma

OBJECTIVE

In light of the upregulation of p21-activated kinase (PAK7) in a variety of cancers, including hepatocellular carcinoma (HCC), we aimed to investigate the effect of PAK7 on the sensitivity of HCC cells to radiotherapy.

METHODS

PAK7 expression was determined in normal adult liver epithelial THLE-2 and human HCC cell lines. The effect of ionizing radiation (IR) on the HCC cell viability was evaluated by Sulforhodamine B (SRB) assay. HCC cell lines Mahlavu and Huh7 were chosen to assess the effect of PAK7 shRNAs on the viability, clone formation, apoptosis, cycle distribution and γ-H2AX expression after exposure to IR.

RESULTS

As compared to THLE-2 cells, PAK7 was upregulated in poorly differentiated Mahlavu and SK-Hep-1 cells, but moderately or lowly expressed in well-differentiated Huh7 and HepG2 cells. HCC cells with moderate or low expression of PAK7 presented a decreased viability at 2 Gy IR, which had no significant effect on PAK7_high HCC cells. Mahlavu and Huh7 cells transfected with PAK7 shRNAs showed increased inhibitory effect of IR on viability. In addition, PAK7 shRNAs reduced clone formation, facilitated the cell apoptosis, arrested cells at G2/M phase, and increased γ-H2AX expression. Moreover, changes above were more evident in the HCC cells co-treated with IR and PAK7 shRNAs.

CONCLUSION

PAK7 downregulation could inhibit the viability, promote the apoptosis, arrest cells in G2/M phase, and induce the DNA damage in HCC cells, thereby enhancing the radiosensitivity in HCC.

Identification of docetaxel-related biomarkers for prostate cancer

Prostate cancer (PCa) which was the second commonly diagnosed malignancy, contributed to the top fifth carcinoma death in men. Nevertheless, the main chemotherapeutic agent docetaxel came to failure due to chemoresistance. Recently, increasing evidence suggested the importance of tumour microenvironment (TME) in PCa. The present study aimed to explore the specific TME in PCa and find biomarkers related to both immune infiltration and docetaxel. The docetaxel-specific genes and differential expression genes comparing PCa with normal control samples were derived using DESeq2 and zinbwave with GSE140440, TCGA and GTEx datasets. Immune-infiltration-related genes were identified using CIBERSORT and co-expression network analysis. Key genes related to both docetaxel and immune infiltrating in PCa, including nine genes, namely ZNF486, IFI6, TMOD2, HSPA4L, ITPR1, LRRC37A7P, APOC1, APOBEC3G, and ITGA2, were determined by overlapping above three gene sets. ITGA2 was then defined as the hub gene for its significant prognostic implications. Further validations conducted on Oncomine, GEO, TISIDB, MSigDB, and The Human Protein Atlas confirmed the docetaxel-specific and immune infiltrating characteristics of ITGA2. To sum up, our findings could provide a better understanding of immune infiltrating and docetaxel-resistance in PCa, mostly, ITGA2 could serve as potential prognosis biomarkers and targets for the combination of docetaxel.

Whole-transcriptome Analysis of Fully Viable Energy Efficient Glycolytic-null Cancer Cells Established by Double Genetic Knockout of Lactate Dehydrogenase A/B or Glucose-6-Phosphate Isomerase

BACKGROUND/AIM

Nearly all mammalian tumors of diverse tissues are believed to be dependent on fermentative glycolysis, marked by elevated production of lactic acid and expression of glycolytic enzymes, most notably lactic acid dehydrogenase (LDH). Therefore, there has been significant interest in developing chemotherapy drugs that selectively target various isoforms of the LDH enzyme. However, considerable questions remain as to the consequences of biological ablation of LDH or upstream targeting of the glycolytic pathway.

MATERIALS AND METHODS

In this study, we explore the biochemical and whole transcriptomic effects of CRISPR-Cas9 gene knockout (KO) of lactate dehydrogenases A and B [LDHA/B double KO (DKO)] and glucose-6-phosphate isomerase (GPI KO) in the human colon cancer cell line LS174T, using Affymetrix 2.1 ST arrays.

RESULTS

The metabolic biochemical profiles corroborate that relative to wild type (WT), LDHA/B DKO produced no lactic acid, (GPI KO) produced minimal lactic acid and both KOs displayed higher mitochondrial respiration, and minimal use of glucose with no loss of cell viability. These findings show a high biochemical energy efficiency as measured by ATP in glycolysis-null cells. Next, transcriptomic analysis conducted on 48,226 mRNA transcripts reflect 273 differentially expressed genes (DEGS) in the GPI KO clone set, 193 DEGS in the LDHA/B DKO clone set with 47 DEGs common to both KO clones. Glycolytic-null cells reflect up-regulation in gene transcripts typically associated with nutrient deprivation / fasting and possible use of fats for energy: thioredoxin interacting protein (TXNIP), mitochondrial 3-hydroxy-3-methylglutaryl-CoA synthase 2 (HMGCS2), PPARγ coactivator 1α (PGC-1α), and acetyl-CoA acyltransferase 2 (ACAA2). Other changes in non-ergometric transcripts in both KOs show losses in "stemness", WNT signaling pathway, chemo/radiation resistance, retinoic acid synthesis, drug detoxification, androgen/estrogen activation, and extracellular matrix reprogramming genes.

CONCLUSION

These findings demonstrate that: 1) The "Warburg effect" is dispensable, 2) loss of the LDHAB gene is not only inconsequential to viability but fosters greater mitochondrial energy, and 3) drugs that target LDHA/B are likely to be ineffective without a plausible combination second drug target.

NBTXR3 Radiotherapy-Activated Functionalized Hafnium Oxide Nanoparticles Show Efficient Antitumor Effects Across a Large Panel of Human Cancer Models

PURPOSE

The side effects of radiotherapy induced on healthy tissue limit its use. To overcome this issue and fully exploit the potential of radiotherapy to treat cancers, the first-in-class radioenhancer NBTXR3 (functionalized hafnium oxide nanoparticles) has been designed to amplify the effects of radiotherapy.

PATIENTS AND METHODS

Thanks to its physical mode of action, NBTXR3 has the potential to be used to treat any type of solid tumor. Here we demonstrate that NBTXR3 can be used to treat a wide variety of solid cancers. For this, we evaluated different parameters on a large panel of human cancer models, such as nanoparticle endocytosis, in vitro cell death induction, dispersion, and retention of NBTXR3 in the tumor tissue and tumor growth control.

RESULTS

Whatever the model considered, we show that NBTXR3 was internalized by cancer cells and persisted within the tumors throughout radiotherapy treatment. NBTXR3 activated by radiotherapy was also more effective in destroying cancer cells and in controlling tumor growth than radiotherapy alone. Beyond the effects of NBTXR3 as single agent, we show that the antitumor efficacy of cisplatin-based chemoradiotherapy treatment was improved when combined with NBTXR3.

CONCLUSION

These data support that NBTXR3 could be universally used to treat solid cancers when radiotherapy is indicated, opening promising new therapeutic perspectives of treatment for the benefit of many patients.

The brominated flame retardants TBECH and DPTE alter prostate growth, histology and gene expression patterns in the mouse

The brominated flame retardants (BFRs), 1,2-dibromo-4-(1,2 dibromoethyl)cyclohexane (TBECH) and 2,3-dibromopropyl-2,4,6-tribromophenyl ether (DPTE) bind to the androgen receptor (AR). in vitro bioassays have shown that TBECH is a potent androgen agonist while DPTE is a potent AR antagonist. Both TBECH and DPTE alter gene expression associated with AR regulation. However, it remains to be determined if TBECH and DPTE can affect the prostate. For this reason, we exposed CD1 mice to a 1:1 mixture of TBECH diastereomers α and β, a 1:1 mixture of γ and δ, and to DPTE, and tested their effects on prostate growth, histology and gene expression profiles. Castrated mice were used to study the androgenic effects of TBECHαβ and TBECHγδ while the antagonistic effects of DPTE were studied in non-castrated mice. We observed that testosterone and TBECHγδ increased body and prostate weights while TBECHαβ affected neither of them; and that DPTE had no effect on body weight but reduced prostate weight drastically. Histomorphometric analysis of the prostate revealed epithelial and glandular alterations in the TBECHγδ group comparable to those in testosterone group while alterations in the TBECHαβ group were less pronounced. DPTE displayed androgen antagonist activity reminiscent of castration. The transcription profile of the prostate was altered by castration and exposure to testosterone and to TBECHγδ reversed several of these changes. Testosterone and TBECHγδ also regulated the expression of several androgen responsive genes implicated in prostate growth and cancer. While DPTE resulted in a drastic reduction in prostate weight, it only affected a small number of genes. The results indicate that TBECHγδ and DPTE are of high human health concern as they may contribute to changes in prostate growth, histology and function.

Effective Prediction of Prostate Cancer Recurrence through the IQGAP1 Network

IQGAP1 expression was analyzed in: (1) primary prostate cancer, (2) xenografts produced from LNCaP, DU145, and PC3 cells, 3) tumor of PTEN-/- and TRAMP mice, and (3) castration resistant PC (CRPC) produced by LNCaP xenografts and PTEN-/- mice. IQGAP1 downregulations occurred in CRPC and advanced PCs. The downregulations were associated with rapid PC recurrence in the TCGA PanCancer (n = 492, p = 0.01) and MSKCC (n = 140, p = 4 × 10-6) cohorts. Differentially expressed genes (n = 598) relative to IQGAP1 downregulation were identified with enrichment in chemotaxis, cytokine signaling, and others along with reductions in immune responses. A novel 27-gene signature (Sig27gene) was constructed from these DEGs through random division of the TCGA cohort into a Training and Testing population. The panel was validated using an independent MSKCC cohort. Sig27gene robustly predicts PC recurrence at (hazard ratio) HR 2.72 and p < 2 × 10-16 in two independent PC cohorts. The prediction remains significant after adjusting for multiple clinical features. The novel and robust nature of Sig27gene underlie its great translational potential as a prognostic biomarker to predict PC relapse risk in patients with primary PC.

Integrative analysis of mRNA and miRNA sequencing data for gliomas of various grades

Background

The purpose of this study was to characterize subtype-specific patterns of mRNA and miRNA expression of gliomas using The Cancer Genome Atlas (TCGA) data to search for genetic determinants that predict prognosis in terms of overall survival and to create interaction networks for grade 2 and 3 (G2 and G3) astrocytomas, oligodendrogliomas and grade 4 (G4) glioblastoma multiforme. Based on open-access TCGA data, 5 groups were formed: astrocytoma G2 (n = 58), astrocytoma G3 (n = 128), oligodendroglioma G2 (n = 102), oligodendroglioma G3 (n = 72) and glioblastoma G4 (n = 564); normal samples of brain tissue were also analysed (n = 15). Data of patient age, sex, survival and expression patterns of mRNA and miRNA were extracted for each sample. After stratification of the data into groups, a differential analysis of expression was carried out, genes and miRNAs that affect overall survival were identified and gene set enrichment analysis (GSEA) and interaction analysis were performed.

Results

A total of 939 samples of glial tumours were analysed, for which subtype-specific expression profiles of genes and miRNAs were identified and networks of mRNA-miRNA interactions were constructed. Genes whose aberrant expression level was associated with survival were determined, and pairwise correlations between differential gene expression (DEG) and differential miRNA expression (DE miRNA) were calculated.

Conclusions

The developed panel of genes and miRNAs allowed us to differentiate glioma subtypes and evaluate prognosis in terms of the overall survival of patients. The regulatory miRNA-mRNA pairs unique to the five glioma subtypes identified in this study can stimulate the development of new therapeutic approaches based on subtype-specific mechanisms of oncogenesis.

Heterotypic signaling between dermal fibroblasts and melanoma cells induces phenotypic plasticity and proteome rearrangement in malignant cells

The signaling events triggered by soluble mediators released from both transformed and stromal cells shape the phenotype of tumoral cells and have significant implications in cancer development and progression. In this study we performed an in vitro heterotypic signaling assays by evaluating the proteome diversity of human dermal fibroblasts after stimulation with the conditioned media obtained from malignant melanoma cells. In addition, we also evaluated the changes in the proteome of melanoma cells after stimulation with their own conditioned media as well as with the conditioned medium from melanoma-stimulated fibroblasts. Our results revealed a clear rearrangement in the proteome of stromal and malignant cells upon crosstalk of soluble mediators. The main proteome signature of fibroblasts stimulated with melanoma conditioned medium was related to protein synthesis, which indicates that this process might be an early response of stromal cells. In addition, the conditioned medium derived from 'primed' stromal cells (melanoma-stimulated fibroblasts) was more effective in altering the functional phenotype (cell migration) of malignant cells than the conditioned medium from non-stimulated fibroblasts. Collectively, self- and cross-stimulation may play a key role in shaping the tumor microenvironment and enable tumoral cells to succeed in the process of melanoma progression and metastasis. Although the proteome landscape of cells participating in such a heterotypic signaling represents a snapshot of a highly dynamic state, understanding the diversity of proteins and enriched biological pathways resulting from stimulated cell states may allow for targeting specific cell regulatory motifs involved in melanoma progression and metastasis.

Integrated analysis of RNA-binding proteins in human colorectal cancer

Background

Although RNA-binding proteins play an essential role in a variety of different tumours, there are still limited efforts made to systematically analyse the role of RNA-binding proteins (RBPs) in the survival of colorectal cancer (CRC) patients.

Methods

Analysis of CRC transcriptome data collected from the TCGA database was conducted, and RBPs were extracted from CRC. R software was applied to analyse the differentially expressed genes (DEGs) of RBPs. To identify related pathways and perform functional annotation of RBP DEGs, Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were carried out using the database for annotation, visualization and integrated discovery. Protein-protein interactions (PPIs) of these DEGs were analysed based on the Search Tool for the Retrieval of Interacting Genes (STRING) database and visualized by Cytoscape software. Based on the Cox regression analysis of the prognostic value of RBPs (from the PPI network) with survival time, the RBPs related to survival were identified, and a prognostic model was constructed. To verify the model, the data stored in the TCGA database were designated as the training set, while the chip data obtained from the GEO database were treated as the test set. Then, both survival analysis and ROC curve verification were conducted. Finally, the risk curves and nomograms of the two groups were generated to predict the survival period.

Results

Among RBP DEGs, 314 genes were upregulated while 155 were downregulated, of which twelve RBPs (NOP14, MRPS23, MAK16, TDRD6, POP1, TDRD5, TDRD7, PPARGC1A, LIN28B, CELF4, LRRFIP2, MSI2) with prognostic value were obtained.

Conclusions

The twelve identified genes may be promising predictors of CRC and play an essential role in the pathogenesis of CRC. However, further investigation of the underlying mechanism is needed.

Survival differences and associated molecular signatures of DNMT3A-mutant acute myeloid leukemia patients

Acute myeloid leukemia (AML) is a very heterogeneous and highly malignant blood cancer. Mutations of the DNA methyltransferase DNMT3A are among the most frequent recurrent genetic lesions in AML. The majority of DNMT3A-mutant AML patients shows fast relapse and poor survival, but also patients with long survival or long-term remission have been reported. Underlying molecular signatures and mechanisms that contribute to these survival differences are only poorly understood and have not been studied in detail so far. We applied hierarchical clustering to somatic gene mutation profiles of 51 DNMT3A-mutant patients from The Cancer Genome Atlas (TCGA) AML cohort revealing two robust patient subgroups with profound differences in survival. We further determined molecular signatures that distinguish both subgroups. Our results suggest that FLT3 and/or NPM1 mutations contribute to survival differences of DNMT3A-mutant patients. We observed an upregulation of genes of the p53, VEGF and DNA replication pathway and a downregulation of genes of the PI3K-Akt pathway in short- compared to long-lived patients. We identified that the majority of measured miRNAs was downregulated in the short-lived group and we found differentially expressed microRNAs between both subgroups that have not been reported for AML so far (miR-153-2, miR-3065, miR-95, miR-6718) suggesting that miRNAs could be important for prognosis. In addition, we learned gene regulatory networks to predict potential major regulators and found several genes and miRNAs with known roles in AML pathogenesis, but also interesting novel candidates involved in the regulation of hematopoiesis, cell cycle, cell differentiation, and immunity that may contribute to the observed survival differences of both subgroups and could therefore be important for prognosis. Moreover, the characteristic gene mutation and expression signatures that distinguished short- from long-lived patients were also predictive for independent DNMT3A-mutant AML patients from other cohorts and could also contribute to further improve the European LeukemiaNet (ELN) prognostic scoring system. Our study represents the first in-depth computational approach to identify molecular factors associated with survival differences of DNMT3A-mutant AML patients and could trigger additional studies to develop robust molecular markers for a better stratification of AML patients with DNMT3A mutations.