Comprehensive Characterization of Androgen-Responsive lncRNAs Mediated Regulatory Network in Hormone-Related Cancers

PRADclass: Hybrid Gleason Grade-Informed Computational Strategy Identifies Consensus Biomarker Features Predictive of Aggressive Prostate Adenocarcinoma

BACKGROUND

Prostate adenocarcinoma (PRAD) is a common cancer diagnosis among men globally, yet large gaps in our knowledge persist with respect to the molecular bases of its progression and aggression. It is mostly indolent and slow-growing, but aggressive prostate cancers need to be recognized early for optimising treatment, with a view to reducing mortality.

METHODS

Based on TCGA transcriptomic data pertaining to PRAD and the associated clinical metadata, we determined the sample Gleason grade, and used it to execute: (i) Gleason-grade wise linear modeling, followed by five contrasts against controls and ten contrasts between grades; and (ii) Gleason-grade wise network modeling via weighted gene correlation network analysis (WGCNA). Candidate biomarkers were obtained from the above analysis and the consensus found. The consensus biomarkers were used as the feature space to train ML models for classifying a sample as benign, indolent or aggressive.

RESULTS

The statistical modeling yielded 77 Gleason grade-salient genes while the WGCNA algorithm yielded 1003 trait-specific key genes in grade-wise significant modules. Consensus analysis of the two approaches identified two genes in Grade-1 (SLC43A1 and PHGR1), 26 genes in Grade-4 (including LOC100128675, PPP1R3C, NECAB1, UBXN10, SERPINA5, CLU, RASL12, DGKG, FHL1, NCAM1, and CEND1), and seven genes in Grade-5 (CBX2, DPYS, FAM72B, SHCBP1, TMEM132A, TPX2, UBE2C). A RandomForest model trained and optimized on these 35 biomarkers for the ternary classification problem yielded a balanced accuracy ∼ 86% on external validation.

CONCLUSIONS

The consensus of multiple parallel computational strategies has unmasked candidate Gleason grade-specific biomarkers. PRADclass, a validated AI model featurizing these biomarkers achieved good performance, and could be trialed to predict the differentiation of prostate cancers. PRADclass is available for academic use at: https://apalania.shinyapps.io/pradclass (online) and https://github.com/apalania/pradclass (command-line interface).

Effect of statins and testosterone replacement therapy on incident cardiovascular disease among male hormone-related cancer survivors

Purpose

Statins and testosterone replacement therapy (TTh) have been previously linked with prostate, colorectal and male breast cancer (hereinafter we will refer as hormone related cancers [HRCa]), and cardiovascular disease (CVD). However, there is a poor understanding about the combined association of statins and TTh with incident CVD among HRCa survivors and a matched cancer-free cohort.

Methods

We identified 44,330 men of whom 22,165 were previously diagnosed with HRCa, and 22,165 were age-and index-matched cancer-free in SEER-Medicare 2007-2015. Pre-diagnostic prescription of statins and TTh prior to CVD development was ascertained for this analysis in the two matched cohorts. Weighted multivariable-adjusted conditional logistic regression models were used to evaluate the independent and combined associations of statins and TTh with CVD.

Results

We found that use of statins (OR = 0.51, 95% CI: 0.46-0.55) and TTh (OR = 0.81, 95% CI: 0.67-0.97) were each independently inversely associated with incident CVD in the overall sample. TTh plus statins was also inversely associated with CVD. Associations were similar in the matched cancer-free cohort. Among HRCa survivors, only statins and combination of TTh plus statins (OR = 0.60, 95% CI: 0.44-0.98) were inversely associated with CVD, but the independent use of TTh was not associated with CVD.

Conclusion

In general, pre-diagnostic use of statins and TTh, prior to CVD development, independently or in combination, were inversely associated with CVD in the overall, cancer-free population, and among HRCa survivors (mainly combination). Independent effects and combination of statins and TTh remained to be confirmed with specific CVD outcomes among HRCa survivors.

Use of weight loss medications in relation with prostate, colorectal and male breast cancers among older men: SEER-Medicare 2007-2015

BACKGROUND

The association of weight loss medications with prostate (PCa), colorectal (CRC) or male breast cancers, including assessment of these cancers combined (HRCs, hormone-associated cancers) remain poorly understood. Testosterone replacement therapy (TTh) is reported to be inversely associated with obesity, PCa and CRC, but it is unclear whether TTh modifies the association of weight loss medications with HRCs.

METHODS

In 49,038 men (≥ 65 years) of SEER-Medicare, we identified 15,471 men diagnosed with PCa, 4836 with CRC, and 141 with male breast cancers. Pre-diagnostic prescription of weight loss medications and TTh was ascertained for this analysis. Weighted multivariable-adjusted conditional logistic and Cox proportional hazards (mortality) models were conducted.

RESULTS

We found an inverse association between use of weight loss medications and incident PCa (OR 0.59, 95% CI 0.57-0.62), CRC (OR 0.86, 95% CI 0.80-0.92), and HRCs (OR 0.65, 95% CI 0.62-0.68). Similar associations were observed for advanced stage at diagnosis of PCa and CRC. Effects of weight loss medications on PCa and HRC remained significant irrespective of the use of TTh but were only suggestive with CRC with positive TTh use. No associations were observed with male breast cancer and HRCs mortality.

CONCLUSION

Pre-diagnostic use of weight loss medications reduced the incidence of PCa, CRC, and HRCs. These associations persisted in the same direction irrespective of the history of TTh use. Future studies are needed to confirm these findings and to identify underlying biological mechanisms of weight loss medications and TTh on the risk of cancer.

LncRNA LINC00969 promotes acquired gefitinib resistance by epigenetically suppressing of NLRP3 at transcriptional and posttranscriptional levels to inhibit pyroptosis in lung cancer

Epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI) treatment prolongs the survival of lung cancer patients harbouring activating EGFR mutations. However, resistance to EGFR-TKIs is inevitable after long-term treatment. Molecular mechanistic research is of great importance in combatting resistance. A comprehensive investigation of the molecular mechanisms underlying resistance has important implications for overcoming resistance. An accumulating body of evidence shows that lncRNAs can contribute to tumorigenesis and treatment resistance. By bioinformatics analysis, we found that LINC00969 expression was elevated in lung cancer cells with acquired gefitinib resistance. LINC00969 regulated resistance to gefitinib in vitro and in vivo. Mechanistically, gain of H3K4me1 and H3K27Ac led to the activation of LINC00969 expression. LINC00969 interacts with EZH2 and METTL3, transcriptionally regulates the level of H3K27me3 in the NLRP3 promoter region, and posttranscriptionally modifies the m6A level of NLRP3 in an m6A-YTHDF2-dependent manner, thus epigenetically repressing NLRP3 expression to suppress the activation of the NLRP3/caspase-1/GSDMD-related classical pyroptosis signalling pathways, thereby endowing an antipyroptotic phenotype and promoting TKI resistance in lung cancer. Our findings provide a new mechanism for lncRNA-mediated TKI resistance from the new perspective of pyroptosis via simultaneous regulation of histone methylation and RNA methylation. The pivotal role of LINC00969 gives it the potential to be a novel biomarker and therapeutic target for overcoming EGFR-TKI resistance in lung cancer.

Identification of androgen response-related lncRNAs in prostate cancer

BACKGROUND

Long noncoding RNAs (lncRNAs) are RNA molecules with over 200 nucleotides that do not code for proteins, but are known to be widely expressed and have key roles in gene regulation and cellular functions. They are also found to be involved in the onset and development of various cancers, including prostate cancer (PCa). Since PCa are commonly driven by androgen regulated signaling, mainly stimulated pathways, identification and determining the influence of lncRNAs in androgen response is useful and necessary. LncRNAs regulated by the androgen receptor (AR) can serve as potential biomarkers for PCa. In the present study, gene expression data analysis were performed to distinguish lncRNAs related to the androgen response pathway.

METHODS AND RESULTS

We used publicly available RNA-sequencing and ChIP-seq data to identify lncRNAs that are associated with the androgen response pathway. Using Universal Correlation Coefficient (UCC) and Pearson Correlation Coefficient (PCC) analyses, we found 15 lncRNAs that have (a) highly correlated expression with androgen response genes in PCa and are (b) differentially expressed in the setting of treatment with an androgen agonist as well as antagonist compared to controls. Using publicly available ChIP-seq data, we investigated the role of androgen/AR axis in regulating expression of these lncRNAs. We observed AR binding in the promoter regions of 5 lncRNAs (MIR99AHG, DUBR, DRAIC, PVT1, and COLCA1), showing the direct influence of AR on their expression and highlighting their association with the androgen response pathway.

CONCLUSION

By utilizing publicly available multiomics data and by employing in silico methods, we identified five candidate lncRNAs that are involved in the androgen response pathway. These lncRNAs should be investigated as potential biomarkers for PCa.

Metformin and testosterone replacement therapy inversely associated with hormone-associated cancers (prostate, colorectal and male breast cancers) among older White and Black men

BACKGROUND

The independent and joint association of metformin and testosterone replacement therapy (TTh) with the incidence of prostate, colorectal, and male breast cancers remain poorly understood, including the investigation of the risk of these cancers combined (HRCs, hormone-associated cancers) among men of different racial and ethnic background.

METHODS

In 143,035 men (≥ 65 yrs old) of SEER-Medicare 2007-2015, we identified White (N = 110,430), Black (N = 13,520) and Other Race (N = 19,085) men diagnosed with incident HRC. Pre-diagnostic prescription of metformin and TTh was ascertained for this analysis. Weighted multivariable-adjusted conditional logistic and Cox proportional hazards models were conducted.

RESULTS

We found independent and joint associations of metformin and TTh with incident prostate (odds ratio [OR]joint  = 0.44, 95% confidence interval [CI]: 0.36-0.54) and colorectal cancers (ORjoint  = 0.47, 95% CI: 0.34-0.64), but not with male breast cancer. There were also inversed joint associations of metformin and TTh with HRCs (ORjoint  = 0.45, 95% CI: 0.38-0.54). Similar reduced associations with HRCs were identified among White, Black, and Other Race men.

CONCLUSION

Pre-diagnostic use of metformin and TTh were, independently and jointly, inversely associated with incident prostate and colorectal cancers. The risk of HRCs was also reduced among White, Black and Other Race men. Greatest reduced associations of prostate and colorectal cancers and HRCs were mainly observed in combination of metformin and TTh. Larger studies are needed to confirm the independent and joint association of metformin plus TTh with these cancers in understudied and underserved populations.

Genetically supported causality between benign prostate hyperplasia and urinary bladder neoplasms: A mendelian randomization study

Background: Observational studies have suggested a possible association between benign prostate hyperplasia (BPH) and bladder cancer (BLCA). However, these studies are prone to errors and limitations or confounding factors, making them unsuitable for assessing the causal relationship between BPH and BLCA. Objective: Two-sample Mendelian randomization (MR) was performed to determine a possible association between genetically predicted BPH and the risk of BLCA. Methods: A two-sample MR analysis was performed utilizing the Integrative Epidemiology Unit genome-wide association (GWAS) database of the Medical Research Council, United Kingdom A series of control steps, including five primary methods, were performed to identify the most suitable instrumental variables (IVs) for MR analysis. Sensitivity analysis was conducted to avoid statistical errors, including heterogeneity and pleiotropic bias. Results: Genetic variants associated with BPH (P < 5 × 10-8) and BLCA (P < 5 × 10-6) were identified as instrumental variables and assessed using GWAS summary data (BPH, 4,670 cases vs. 458,340 controls; BLCA, 1,279 cases vs. 372,016 controls). BPH exhibited a positive effect on the occurrence of BLCA (inverse variance weighted (IVW), odds ratio (OR) = 1.095, 95% confidence interval (CI) = 1.030-1.165, p = 0.003), but there was no causal effect for BLCA on BPH (IVW, OR = 1.092, 95% CI = 0.814-1.465, p = 0.554). Conclusion: Genetically predicted BPH was associated with a higher risk of BLCA in all histological subtypes. In contrast, the evidence was not significant to back the causality of genetically induced BLCA on BPH. These findings indicate that BPH plays a key role in developing BLCA in the European population. Further studies are needed to uncover the underlying mechanisms.

Development and Validation of Lactate Metabolism-Related lncRNA Signature as a Prognostic Model for Lung Adenocarcinoma

BACKGROUND

Lung cancer has been a prominent research focus in recent years due to its role in cancer-related fatalities globally, with lung adenocarcinoma (LUAD) being the most prevalent histological form. Nonetheless, no signature of lactate metabolism-related long non-coding RNAs (LMR-lncRNAs) has been developed for patients with LUAD. Accordingly, we aimed to develop a unique LMR-lncRNA signature to determine the prognosis of patients with LUAD.

METHOD

The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were utilized to derive the lncRNA expression patterns. Identification of LMR-lncRNAs was accomplished by analyzing the co-expression patterns between lncRNAs and LMR genes. Subsequently, the association between lncRNA levels and survival outcomes was determined to develop an effective signature. In the TCGA cohort, Cox regression was enlisted to build an innovative signature consisting of three LMR-lncRNAs, which was validated in the GEO validation cohort. GSEA and immune infiltration analysis were conducted to investigate the functional annotation of the signature and the function of each type of immune cell.

RESULTS

Fourteen differentially expressed LMR-lncRNAs were strongly correlated with the prognosis of patients with LUAD and collectively formed a new LMR-lncRNA signature. The patients could be categorized into two cohorts based on their LMR-lncRNA signatures: a low-risk and high-risk group. The overall survival of patients with LUAD in the high-risk group was considerably lower than those in the low-risk group. Using Cox regression, this signature was shown to have substantial potential as an independent prognostic factor, which was further confirmed in the GEO cohort. Moreover, the signature could anticipate survival across different groups based on stage, age, and gender, among other variables. This signature also correlated with immune cell infiltration (including B cells, neutrophils, CD4⁺ T cells, CD8⁺ T cells, etc.) as well as the immune checkpoint blockade target CTLA-4.

CONCLUSION

We developed and verified a new LMR-lncRNA signature useful for anticipating the survival of patients with LUAD. This signature could give potentially critical insight for immunotherapy interventions in patients with LUAD.

Isolating and culturing of single microbial cells by laser ejection sorting technology

Single cell isolation and cultivation play an important role in studying physiology, gene expression and functions of microorganisms. A series of single-cell isolation technologies have been developed, among which single-cell ejection technology is one of the most promising. Single cell ejection technology has applied Laser Induced Forward Transfer Technique (LIFT) to isolate bacteria but the viability (or recovery rate) of cells after sorting has not been clarified in the current research progress. In this work, to keep the cells alive as much as possible, we propose a three-layer LIFT system (top layer: 25-nm aluminum film; second layer: 3 μm agar media; third layer: liquid containing bacterial) for the isolation and cultivation of single Gram-negative (E. coli), Gram-positive (Lactobacillus rhamnosus GG, LGG), and eukaryotic microorganisms (Saccharomyces cerevisiae). The experiment results showed that the average survival rates for ejected pure single cells were 63% for Saccharomyces cerevisiae, 22% for E. coli DH5α, and 74% for LGG. In addition, we successfully isolated and cultured the GFP expressing E. coli JM109 from the mixture containing complex communities of soil bacteria by fluorescence signal. The average survival rate of E. coli JM109 was demonstrated to be 25.3%. In this study, the isolated and cultured single colonies were further confirmed by colony PCR and sequencing. Such precise sorting and cultivation technique of live single microbial cells could be coupled with other microscopic approaches to isolate single microorganisms with specific functions, revealing their roles in the natural community. Importance We developed a laser induced forward transfer (LIFT) technology to accurately isolate single live microbial cells. The cultivation recovery rates of the ejected single cells were 63% for Saccharomyces cerevisiae, 22% for E. coli DH5α, and 74% for Lactobacillus rhamnosus GG (LGG). Coupled LIFT with fluorescent microscope, we demonstrated that single cells of GFP expressing E. coli JM109 were sorted according to fluorescence signal from a complex community of soil bacteria, and subsequently cultured with 25% cultivation recovery rate. This single cell live sorting technology could isolate single microbes with specific functions, revealing their roles in the natural community.

Investigation of the lncRNA THOR in Mice Highlights the Importance of Noncoding RNAs in Mammalian Male Reproduction

THOR is a highly conserved testis-specific long noncoding RNA (lncRNA). The interaction between THOR and the development of the male reproductive system remains unclear. Herein, CRISPR/Cas9 technology was used to establish a stable THOR-deficient mouse model, and the relationship between THOR and the fertility of adult male mice was investigated. The male mice in which THOR was deleted were smaller than the WT male mice. Moreover, their survival rate was reduced by 60%, their fertility was reduced by 50%, their testicular size and sperm motility were reduced by 50%, their testicular cell apoptosis was increased by 7-fold, and their ratio of female-to-male offspring was imbalanced (approximately 1:3). Furthermore, to elucidate the mechanisms of male reproductive system development, the mRNA levels of THOR targets were measured by qRT-PCR. Compared with WT mice, the THOR-deficient mice exhibited significantly decreased mRNA levels of IGF2BP1, c-MYC, IGF1, and IGF2. MEK-ERK signaling pathway expression was downregulated as determined by Western blot. We found that THOR targeted the MER-ERK signaling pathway downstream of IGF2 by binding to IGF2BP1 and affected testicular and sperm development in male mice. These results may also provide perspectives for exploring the roles of lncRNAs in human reproductive development and the pathogenesis and potential therapeutic targets of infertility.

A seven-lncRNA signature for predicting Ewing's sarcoma

Background

Long non-coding RNAs (lncRNAs) are a class of non-coding RNAs with unique characteristics. These RNA can regulate cancer cells’ survival, proliferation, invasion, metastasis, and angiogenesis and are potential diagnostic and prognostic markers. We identified a seven-lncRNA signature related to the overall survival (OS) of patients with Ewing’s sarcoma (EWS).

Methods

We used an expression profile from the Gene Expression Omnibus (GEO) database as a training cohort to screen out the OS-associated lncRNAs in EWS and further established a seven-lncRNA signature using univariate Cox regression, the least absolute shrinkage, and selection operator (LASSO) regression analysis. The prognostic lncRNA signature was validated in an external dataset from the International Cancer Genome Consortium (ICGC) as a validation cohort.

Results

We obtained 10 survival-related lncRNAs from the Kaplan-Meier and ROC curve analysis (log-rank test P < 0.05; AUC >0.6). Univariate Cox regression and LASSO regression analyses confirmed seven key lncRNAs and we established a lncRNA signature to predict an EWS prognosis. EWS patients in the training cohort were categorized into a low-risk group or a high-risk group based on their median risk score. The high-risk group’s survival time was significantly shorter than the low-risk group’s. This seven-lncRNA signature was further confirmed by the validation cohort. The area under the curve (AUC) for this lncRNA signature was up to 0.905 in the training group and 0.697 in the 3-year validation group. The nomogram’s calibration curves demonstrated that EWS probability in the two cohorts was consistent between the nomogram prediction and actual observation.

Conclusion

We screened a seven-lncRNA signature to predict the EWS patients’ prognosis. Our findings provide a new reference for the current prognostic evaluation of EWS and new direction for the diagnosis and treatment of EWS.

The Role of Androgens and Androgen Receptor in Human Bladder Cancer

Bladder cancer (urothelial carcinoma) is one of the most frequently diagnosed neoplasms, with an estimated half a million new cases and 200,000 deaths per year worldwide. This pathology mainly affects men. Men have a higher risk (4:1) of developing bladder cancer than women. Cigarette smoking and exposure to chemicals such as aromatic amines, and aniline dyes have been established as risk factors for bladder cancer and may contribute to the sex disparity. Male internal genitalia, including the urothelium and prostate, are derived from urothelial sinus endoderm; both tissues express the androgen receptor (AR). Several investigations have shown evidence that the AR plays an important role in the initiation and development of different types of cancer including bladder cancer. In this article, we summarize the available data that help to explain the role of the AR in the development and progression of bladder cancer, as well as the therapies used for its treatment.

Deciphering the Methylation Landscape in Breast Cancer: Diagnostic and Prognostic Biosignatures through Automated Machine Learning

DNA methylation plays an important role in breast cancer (BrCa) pathogenesis and could contribute to driving its personalized management. We performed a complete bioinformatic analysis in BrCa whole methylome datasets, analyzed using the Illumina methylation 450 bead-chip array. Differential methylation analysis vs. clinical end-points resulted in 11,176 to 27,786 differentially methylated genes (DMGs). Innovative automated machine learning (AutoML) was employed to construct signatures with translational value. Three highly performing and low-feature-number signatures were built: (1) A 5-gene signature discriminating BrCa patients from healthy individuals (area under the curve (AUC): 0.994 (0.982-1.000)). (2) A 3-gene signature identifying BrCa metastatic disease (AUC: 0.986 (0.921-1.000)). (3) Six equivalent 5-gene signatures diagnosing early disease (AUC: 0.973 (0.920-1.000)). Validation in independent patient groups verified performance. Bioinformatic tools for functional analysis and protein interaction prediction were also employed. All protein encoding features included in the signatures were associated with BrCa-related pathways. Functional analysis of DMGs highlighted the regulation of transcription as the main biological process, the nucleus as the main cellular component and transcription factor activity and sequence-specific DNA binding as the main molecular functions. Overall, three high-performance diagnostic/prognostic signatures were built and are readily available for improving BrCa precision management upon prospective clinical validation. Revisiting archived methylomes through novel bioinformatic approaches revealed significant clarifying knowledge for the contribution of gene methylation events in breast carcinogenesis.