Reference-free transcriptome exploration reveals novel RNAs for prostate cancer diagnosis

Highly sensitive deep panel sequencing of 27 HPV genotypes in prostate cancer biopsies results in very low detection rates and indicates that HPV is not a major etiological driver of this malignancy

BACKGROUND

Human papillomavirus (HPV) has been proposed to contribute to the carcinogenesis of prostate cancer. However, previous studies have yielded conflicting results. This study aims to add useful information to the ongoing discussion concerning the association between HPV infection and prostate cancer.

METHODS

We used two high-throughput next-generation sequencing (NGS) approaches to detect HPV RNA in malignant and adjacent normal (AN) prostate tissue (cohorts 1 and 2) and HPV DNA from carcinogenic and probably/possibly carcinogenic-classified HPV types (cohort 3) in malignant prostate, AN prostate, and benign prostatic hyperplasia (BPH) tissues.

RESULTS

In total, 0% (cohort 1: 0/83, cohort 2: 0/16) of the malignant prostate tissue samples and 0% (cohort 1: 0/23, cohort 2: 0/8) of the AN prostate tissue samples were positive for HPV RNA. A total of 8.3% (1/12) of the BPH samples, 0% (0/28) of the AN samples, and 0.8% (1/132) of the malignant prostate samples were positive for HPV16 DNA. However, the normalized read count of the HPV16-positive malignant sample was close to the cut-off. In addition, no other carcinogenic-classified HPV types were detected in any of the BPH, AN, or malignant prostate tissue samples.

CONCLUSION

Our study does not support HPV infection as a major contributor to the etiology of prostate cancer.

An Atlas of Accessible Chromatin in Advanced Prostate Cancer Reveals the Epigenetic Evolution during Tumor Progression

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal disease that resists therapy targeting androgen signaling, the primary driver of prostate cancer. mCRPC resists androgen receptor (AR) inhibitors by amplifying AR signaling or by evolving into therapy-resistant subtypes that do not depend on AR. Elucidation of the epigenetic underpinnings of these subtypes could provide important insights into the drivers of therapy resistance. In this study, we produced chromatin accessibility maps linked to the binding of lineage-specific transcription factors (TF) by performing assay for transposase-accessible chromatin sequencing on 70 mCRPC tissue biopsies integrated with transcriptome and whole-genome sequencing. mCRPC had a distinct global chromatin accessibility profile linked to AR function. Analysis of TF occupancy across accessible chromatin revealed 203 TFs associated with mCRPC subtypes. Notably, ZNF263 was identified as a putative prostate cancer TF with a significant impact on gene activity in the double-negative subtype (AR- neuroendocrine-), potentially activating MYC targets. Overall, this analysis of chromatin accessibility in mCRPC provides valuable insights into epigenetic changes that occur during progression to mCRPC. Significance: Integration of a large cohort of transcriptome, whole-genome, and ATAC sequencing characterizes the chromatin accessibility changes in advanced prostate cancer and identifies therapy-resistant prostate cancer subtype-specific transcription factors that modulate oncogenic programs.

Integrative analysis of ultra-deep RNA-seq reveals alternative promoter usage as a mechanism of activating oncogenic programmes during prostate cancer progression

Transcription factor (TF) proteins regulate gene activity by binding to regulatory regions, most importantly at gene promoters. Many genes have alternative promoters (APs) bound by distinct TFs. The role of differential TF activity at APs during tumour development is poorly understood. Here we show, using deep RNA sequencing in 274 biopsies of benign prostate tissue, localized prostate tumours and metastatic castration-resistant prostate cancer, that AP usage increases as tumours progress and APs are responsible for a disproportionate amount of tumour transcriptional activity. Expression of the androgen receptor (AR), the key driver of prostate tumour activity, is correlated with elevated AP usage. We identified AR, FOXA1 and MYC as potential drivers of AP activation. DNA methylation is a likely mechanism for AP activation during tumour progression and lineage plasticity. Our data suggest that prostate tumours activate APs to magnify the transcriptional impact of tumour drivers, including AR and MYC.

Exploring the enigma: history, present, and future of long non-coding RNAs in cancer

Long noncoding RNAs (lncRNAs), which are more than 200 nucleotides in length and do not encode proteins, play crucial roles in governing gene expression at both the transcriptional and posttranscriptional levels. These molecules demonstrate specific expression patterns in various tissues and developmental stages, suggesting their involvement in numerous developmental processes and diseases, notably cancer. Despite their widespread acknowledgment and the growing enthusiasm surrounding their potential as diagnostic and prognostic biomarkers, the precise mechanisms through which lncRNAs function remain inadequately understood. A few lncRNAs have been studied in depth, providing valuable insights into their biological activities and suggesting emerging functional themes and mechanistic models. However, the extent to which the mammalian genome is transcribed into functional noncoding transcripts is still a matter of debate. This review synthesizes our current understanding of lncRNA biogenesis, their genomic contexts, and their multifaceted roles in tumorigenesis, highlighting their potential in cancer-targeted therapy. By exploring historical perspectives alongside recent breakthroughs, we aim to illuminate the diverse roles of lncRNA and reflect on the broader implications of their study for understanding genome evolution and function, as well as for advancing clinical applications.

The Genomic and Epigenomic Landscape of Double-Negative Metastatic Prostate Cancer

Systemic targeted therapy in prostate cancer is primarily focused on ablating androgen signaling. Androgen deprivation therapy and second-generation androgen receptor (AR)-targeted therapy selectively favor the development of treatment-resistant subtypes of metastatic castration-resistant prostate cancer (mCRPC), defined by AR and neuroendocrine (NE) markers. Molecular drivers of double-negative (AR-/NE-) mCRPC are poorly defined. In this study, we comprehensively characterized treatment-emergent mCRPC by integrating matched RNA sequencing, whole-genome sequencing, and whole-genome bisulfite sequencing from 210 tumors. AR-/NE- tumors were clinically and molecularly distinct from other mCRPC subtypes, with the shortest survival, amplification of the chromatin remodeler CHD7, and PTEN loss. Methylation changes in CHD7 candidate enhancers were linked to elevated CHD7 expression in AR-/NE+ tumors. Genome-wide methylation analysis nominated Krüppel-like factor 5 (KLF5) as a driver of the AR-/NE- phenotype, and KLF5 activity was linked to RB1 loss. These observations reveal the aggressiveness of AR-/NE- mCRPC and could facilitate the identification of therapeutic targets in this highly aggressive disease.

SIGNIFICANCE

Comprehensive characterization of the five subtypes of metastatic castration-resistant prostate cancer identified transcription factors that drive each subtype and showed that the double-negative subtype has the worst prognosis.

Pro-tumorigenic role of lnc-ZNF30-3 as a sponge counteracting miR-145-5p in prostate cancer

BACKGROUND

Prostate cancer remains one of the deadliest neoplasms in developed countries. Identification of new molecular markers that predict the onset and progression of the disease could improve its clinical management. Low miR-145-5p expression is consistently found in primary tumors and metastases, but the regulatory mechanisms governing its functions remain largely unknown.

METHODS

Bioinformatics analysis was conducted to identify [1] a set of novel potential competing endogenous lncRNAs for sponging of miRNA-145-5p in prostate cancer and [2] miR-145-5p and other EMT-related miRNAs response elements in lnc-ZNF30-3. Quantification of miR-145-5p, lnc-ZNF30-3, and TWIST1 expression levels in tumor tissues in RNA sequencing datasets of our and TCGA PRAD cohorts revealed a correlation with clinical outcome of prostate cancer patients. Biochemical and cell biology approaches, such as RNA pull-down, western blot, immunostaining, and wound healing assays were used for evaluation of the impact of TWIST1/miR-145/ lnc-ZNF30-3 interactions in prostate cancer cells altered in miRNA and lncRNA expression.

RESULTS

We identified a few potential lncRNA sponges of miR-145-5p, including lnc-ZNF30-3. It contains five response elements for miR-145-5p, but also other miRNAs targeting EMT transcription factors. Lnc-ZNF30-3 is significantly upregulated in prostate cancer cell lines and tumor tissues, and its high expression is correlated with poor patient prognosis. We demonstrated that lnc-ZNF30-3 is associated with AGO2 and specifically interacts with the miR-145-5p seed region. Knockdown of lnc-ZNF30-3 results in decreased migration of prostate cancer cells and downregulation of EMT drivers such as TWIST1 and ZEB1 at both the RNA and protein levels. These phenotypic and molecular features of lnc-ZNF30-3-depleted cells are partially rescued by miR-145-5p inhibition.

CONCLUSIONS

Collectively, our results point to lnc-ZNF30-3 as a novel competing endogenous lncRNA for miR-145-5p and other miRNAs that target TWIST1 as well as other EMT transcription factors. Prostate cancer patients with high lncRNA expression in primary tumors show lower survival rate suggesting that lnc-ZNF30-3 may contribute to prostate cancer progression and metastasis.

RATTLE: reference-free reconstruction and quantification of transcriptomes from Nanopore sequencing

Nanopore sequencing enables the efficient and unbiased measurement of transcriptomes. Current methods for transcript identification and quantification rely on mapping reads to a reference genome, which precludes the study of species with a partial or missing reference or the identification of disease-specific transcripts not readily identifiable from a reference. We present RATTLE, a tool to perform reference-free reconstruction and quantification of transcripts using only Nanopore reads. Using simulated data and experimental data from isoform spike-ins, human tissues, and cell lines, we show that RATTLE accurately determines transcript sequences and their abundances, and shows good scalability with the number of transcripts.

Urinary extracellular vesicles contain mature transcriptome enriched in circular and long noncoding RNAs with functional significance in prostate cancer

Long noncoding (lnc)RNAs modulate gene expression alongside presenting unexpected source of neoantigens. Despite their immense interest, their ability to be transferred and control adjacent cells is unknown. Extracellular Vesicles (EVs) offer a protective environment for nucleic acids, with pro and antitumourigenic functions by controlling the immune response. In contrast to extracellular nonvesicular RNA, few studies have addressed the full RNA content within human fluids' EVs and have compared them with their tissue of origin. Here, we performed Total RNA-Sequencing on six Formalin-Fixed-Paraffin-Embedded (FFPE) prostate cancer (PCa) tumour tissues and their paired urinary (u)EVs to provide the first whole transcriptome comparison from the same patients. UEVs contain simplified transcriptome with intron-free cytoplasmic transcripts and enriched lnc/circular (circ)RNAs, strikingly common to an independent 20 patients' urinary cohort. Our full cellular and EVs transcriptome comparison within three PCa cell lines identified a set of overlapping 14 uEV-circRNAs characterized as essential for prostate cell proliferation in vitro and 28 uEV-lncRNAs belonging to the cancer-related lncRNA census (CLC2). In addition, we found 15 uEV-lncRNAs, predicted to encode 768 high-affinity neoantigens, and for which three of the encoded-ORF produced detectable unmodified peptides by mass spectrometry. Our dual analysis of EVs-lnc/circRNAs both in urines' and in vitro's EVs provides a fundamental resource for future uEV-lnc/circRNAs phenotypic characterization involved in PCa.

Overexpression of Nucleolin and Associated Genes in Prostate Cancer

Prostate cancer (PCa) is the second most frequent cancer and the fifth leading cause of cancer death in men worldwide. If local PCa presents a favorable prognosis, available treatments for advanced PCa display limiting benefits due to therapeutic resistances. Nucleolin (NCL) is a ubiquitous protein involved in numerous cell processes, such as ribosome biogenesis, cell cycles, or angiogenesis. NCL is overexpressed in several tumor types in which it has been proposed as a diagnostic and prognostic biomarker. In PCa, NCL has mainly been studied as a target for new therapeutic agents. Nevertheless, little data are available concerning its expression in patient tissues. Here, we investigated the expression of NCL using a new cohort from Mondor Hospital and data from published cohorts. Results were then compared with NCL expression using in vitro models. NCL was overexpressed in PCa tissues compared to the normal tissues, but no prognostic values were demonstrated. Nine genes were highly co-expressed with NCL in patient tissues and tumor prostate cell lines. Our data demonstrate that NCL is an interesting diagnostic biomarker and propose a signature of genes co-expressed with NCL.

Microbiota of the prostate tumor environment investigated by whole-transcriptome profiling

Background

With over 350,000 estimated deaths worldwide in 2018, prostate cancer (PCa) continues to be a major health concern and a significant cause of cancer-associated mortality among men. While cancer in general is considered a disease of the human genome, there is a growing body of evidence suggesting that changes to the healthy microbiota could play a vital role in cancer development, progression, and/or treatment outcome.

Methods

Using a metatranscriptomic approach, we annotated the microbial reads obtained from total RNA sequencing of 106 prostate tissue samples from 94 PCa patients (discovery cohort). We investigated microbial dysbiosis associated with PCa by systematically comparing the microbiomes between benign and malignant tissue samples, between less vs. more-aggressive PCa, and between patients who had biochemical recurrence as opposed to those who did not. We further performed differential gene expression and cell type enrichment analysis to explore the host transcriptomic and cellular responses to selected microbial genera. A public dataset (GSE115414) of total RNA sequencing reads from 24 prostate tissue samples (8 benign and 16 malignant) served as the validation cohort.

Results

We observed decreased species diversity and significant under-representation of Staphylococcus saprophyticus and Vibrio parahaemolyticus, as well as significant over-abundance of Shewanella in malignant as compared to benign prostate tissue samples in both the discovery (p < 0.01) and validation (p < 0.05) cohorts. In addition, we identified Microbacterium species (p < 0.01) to be significantly over-abundant in pathologically advanced T3 tumors compared to T2 in the discovery cohort. Malignant samples having high vs. low Shewanella counts were associated with downregulated Toll-like receptor signaling pathways and decreased enrichment of dendritic cells. Malignant samples having low vs. high V. parahaemolyticus counts were enriched for olfactory transduction and drug metabolism pathways. Finally, malignant samples were enriched for M1 and M2 macrophages as compared to benign tissue samples.

Conclusions

The results from this exploratory study support the existence of an important biological link between the prostate microbiota and PCa development/progression. Our results highlight Shewanella, V. parahaemolyticus, and Microbacterium sp. as interesting candidates for further investigation of their association with PCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01011-3.

Reference-free transcriptome signatures for prostate cancer prognosis

BACKGROUND

RNA-seq data are increasingly used to derive prognostic signatures for cancer outcome prediction. A limitation of current predictors is their reliance on reference gene annotations, which amounts to ignoring large numbers of non-canonical RNAs produced in disease tissues. A recently introduced kind of transcriptome classifier operates entirely in a reference-free manner, relying on k-mers extracted from patient RNA-seq data.

METHODS

In this paper, we set out to compare conventional and reference-free signatures in risk and relapse prediction of prostate cancer. To compare the two approaches as fairly as possible, we set up a common procedure that takes as input either a k-mer count matrix or a gene expression matrix, extracts a signature and evaluates this signature in an independent dataset.

RESULTS

We find that both gene-based and k-mer based classifiers had similarly high performances for risk prediction and a markedly lower performance for relapse prediction. Interestingly, the reference-free signatures included a set of sequences mapping to novel lncRNAs or variable regions of cancer driver genes that were not part of gene-based signatures.

CONCLUSIONS

Reference-free classifiers are thus a promising strategy for the identification of novel prognostic RNA biomarkers.

A Gleason score-related outcome model for human prostate cancer: a comprehensive study based on weighted gene co-expression network analysis

BACKGROUND

Prostate cancer (PCa) is the second leading cause of cancer death in men in 2018. Thus, the evaluation of prognosis is crucial for clinical treatment decision of human PCa patients. We aim to establishing an effective and reliable model to predict the outcome of PCa patients.

METHODS

We first identified differentially expressed genes between prostate cancer and normal prostate in TCGA-PRAD and then performed WGCNA to initially identify the candidate Gleason score related genes. Then, the candidate genes were applied to construct a LASSO Cox regression analysis model. Numerous independent validation cohorts, time-dependent receiver operating characteristic (ROC), univariate cox regression analysis, nomogram were used to test the effectiveness, accuracy and clinical utility of the prognostic model. Furthermore, functional analysis and immune cells infiltration were performed.

RESULTS

Gleason score-related differentially expressed candidates were identified and used to build up the outcome model in TCGA-PRAD cohort and was validated in MSKCC cohort. We found the 3-gene outcome model (CDC45, ESPL1 and RAD54L) had good performance in predicting recurrence free survival, metastasis free survival and overall survival of PCa patients. Time-dependent ROC and nomogram indicated an ideal predictive accuracy and clinical utility of the outcome model. Moreover, outcome model was enriched in 28 pathways by GSVA and GSEA. In addition, the risk score was positively correlated with memory B cells, native CD4 T cells, activated CD4 memory T cells and eosinophil, and negatively correlated with plasma cells, resting CD4 memory T cells, resting mast cells and neutrophil.

CONCLUSIONS

In summary, our outcome model proves to be an effective prognostic model for predicting the risk of prognosis in PCa.

Long non-coding RNA FER1L4 inhibits prostate cancer progression via sponging miR-92a-3p and upregulation of FBXW7

Background

Dysregulation of long non-coding RNAs (lncRNAs) is involved in development of prostate cancer. However, the molecular mechanisms of many lncRNAs in prostate cancer have not been studied yet.

Methods

The lncRNA Fer-1-like protein 4 (FER1L4) expression was explored in prostate tumors and normal prostate tissues by RT-qPCR and bioinformatic analysis. Overexpression of FER1L4 was performed to evaluate its role in prostate cancer cell proliferation and survival. The molecular mechanism of FER1L4 was investigated by dual luciferase reporter assay, RNA pull down assay, western blotting and RT-qPCR.

Results

It was found that FER1L4 was lower in prostate cancer tissues than normal tissues. Higher expression of FER1L4 was associated with prostate cancer tissues of early stage (AJCC stage I/II). Overexpression of FER1L4 inhibited cell proliferation and promoted cell apoptosis in prostate cancer cells. Bioinformatic analysis, RT-qPCR, RNA pull down assay and dual luciferase assay showed that FER1L4 upregulated F-box/WD repeat-containing protein 7 (FBXW7) tumor suppressor via sponging miR-92a-3p. Silencing of FBXW7 reversed the cell phenotypes caused by FER1L4 overexpression in prostate cancer cells.

Conclusion

The data demonstrated that FER1L4, a downregulated lncRNA in prostate cancer, was pivotal for cell proliferation and survival of prostate cancer. The study provided new sights into understanding of the signaling network in prostate cancer and implied that FER1L4 might be a biomarker for patients with prostate cancer.