Significance of the TMPRSS2:ERG gene fusion in prostate cancer

Oncogenic gene fusions in cancer: from biology to therapy

Oncogenic gene fusions occur across a broad range of cancers and are a defining feature of some cancer types. Cancers driven by gene fusion products tend to respond well to targeted therapies, where available; thus, detection of potentially targetable oncogenic fusions is necessary to select optimal treatment. Detection methods include non-sequencing methods, such as fluorescence in situ hybridization and immunohistochemistry, and sequencing methods, such as DNA- and RNA-based next-generation sequencing (NGS). While NGS is an efficient way to analyze multiple genes of interest at once, economic and technical factors may preclude its use in routine care globally, despite several guideline recommendations. The aim of this review is to present a summary of oncogenic gene fusions, with a focus on fusions that affect tyrosine kinase signaling, and to highlight the importance of testing for oncogenic fusions. We present an overview of the identification of oncogenic gene fusions and therapies approved for the treatment of cancers harboring gene fusions, and summarize data regarding treating fusion-positive cancers with no current targeted therapies and clinical studies of fusion-positive cancers. Although treatment options may be limited for patients with rare alterations, healthcare professionals should identify patients most likely to benefit from oncogenic gene fusion testing and initiate the appropriate targeted therapy to achieve optimal treatment outcomes.

Accurate fusion transcript identification from long- and short-read isoform sequencing at bulk or single-cell resolution

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics and prognostics and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short-read sequences. Recent advances in long-read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single-cell samples. Here, we developed a new computational tool, CTAT-LR-Fusion, to detect fusion transcripts from long-read RNA-seq with or without companion short reads, with applications to bulk or single-cell transcriptomes. We demonstrate that CTAT-LR-Fusion exceeds the fusion detection accuracy of alternative methods as benchmarked with simulated and genuine long-read RNA-seq. Using short- and long-read RNA-seq, we further apply CTAT-LR-Fusion to bulk transcriptomes of nine tumor cell lines and to tumor single cells derived from a melanoma sample and three metastatic high-grade serous ovarian carcinoma samples. In both bulk and single-cell RNA-seq, long isoform reads yield higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-Fusion, we are able to further maximize the detection of fusion splicing isoforms and fusion-expressing tumor cells.

Transcriptomics in the era of long-read sequencing

Transcriptome sequencing revolutionized the analysis of gene expression, providing an unbiased approach to gene detection and quantification that enabled the discovery of novel isoforms, alternative splicing events and fusion transcripts. However, although short-read sequencing technologies have surpassed the limited dynamic range of previous technologies such as microarrays, they have limitations, for example, in resolving full-length transcripts and complex isoforms. Over the past 5 years, long-read sequencing technologies have matured considerably, with improvements in instrumentation and analytical methods, enabling their application to RNA sequencing (RNA-seq). Benchmarking studies are beginning to identify the strengths and limitations of long-read RNA-seq, although there remains a need for comprehensive resources to guide newcomers through the intricacies of this approach. In this Review, we provide a comprehensive overview of the long-read RNA-seq workflow, from library preparation and sequencing challenges to core data processing, downstream analyses and emerging developments. We present an extensive inventory of experimental and analytical methods and discuss current challenges and prospects.

TMPRSS2::ETS translocation in nonprostatic malignancies: an unexpected finding in thymic carcinoma and pulmonary adenocarcinoma

TMPRSS2::ETS fusions occur in about half of the prostate adenocarcinomas and are generally considered characteristic and even diagnostic of this tumour. Despite this fact, the frequency of this fusion is not well established in other tumour types. Incidental identification of a TMPRSS2::ETV1 fusion in a thymic squamous cell carcinoma prompted us to assess 1758 solid tumours by next-generation sequencing panel for TMPRSS2::ETS fusions, including 1690 non-prostatic malignancies. In addition to 28 of the 68 prostatic adenocarcinomas, we identified TMPRRS2::ETS fusion in two non-prostatic tumours, where a prostatic adenocarcinoma could be confidently excluded. Besides the TMPRSS2::ETV1 fusion identified in the thymic carcinoma, we also observed TMPRSS2::ERG fusion in pulmonary adenocarcinoma. Both patients were male, which would support an androgen-driven background. Our findings suggest that although at a low frequency, TMPRSS2::ETS fusion may occur in non-prostatic tumours, and sole reliance on its identification can potentially result in erroneous diagnostic conclusions.

Prostate Cancer: A Journey Through Its History and Recent Developments

Prostate cancer is one of the most common diseases among men worldwide and continues to pose a serious threat to health. This review shows the history and the new developments in the management of prostate cancer, with an emphasis on a range of therapeutic approaches, such as hormone therapy, radiation therapy, surgery, and innovative targeted therapeutics. The evolution of these treatments is examined in light of clinical outcomes, patient quality of life, and emerging resistance mechanisms, such as the recently shown vitamin D-based strategies. New developments that have the potential to increase survival rates and reduce side effects are also discussed, including PARP inhibitors (PARPis), immunotherapy, and tailored medication. Additionally, the use of biomarkers and sophisticated imaging methods in therapeutic decision-making is explored, with a focus on how these tools might improve patient care. The absolute necessity for a multidisciplinary approach for improving treatment strategies is becoming more and more apparent as our understanding of the biology of prostate cancer deepens. This approach ensures that patients receive customized medicines that fit their unique profiles. Future avenues of investigation will focus on resolving issues dealing with treatment efficacy and resistance to improve treatment results, ultimately leading to disease cure for prostate cancer patients.

Unveiling the molecular profile of a prostate carcinoma: implications for personalized medicine

BACKGROUND

Prostate cancer is the most common diagnosed tumor and the fifth cancer related death among men in Europe. Although several genetic alterations such as ERG-TMPRSS2 fusion, MYC amplification, PTEN deletion and mutations in p53 and BRCA2 genes play a key role in the pathogenesis of prostate cancer, specific gene alteration signature that could distinguish indolent from aggressive prostate cancer or may aid in patient stratification for prognosis and/or clinical management of patients with prostate cancer is still missing. Therefore, here, by a multi-omics approach we describe a prostate cancer carrying the fusion of TMPRSS2 with ERG gene and deletion of 16q chromosome arm.

RESULTS

We have observed deletion of KDM6A gene, which may represent an additional genomic alteration to be considered for patient stratification. The cancer hallmarks gene signatures highlight intriguing molecular aspects that characterize the biology of this tumor by both a high hypoxia and immune infiltration scores. Moreover, our analysis showed a slight increase in the Tumoral Mutational Burden, as well as an over-expression of the immune checkpoints. The omics profiling integrating hypoxia, ROS and the anti-cancer immune response, optimizes therapeutic strategies and advances personalized care for prostate cancer patients.

CONCLUSION

The here data reported can lay the foundation for predicting a poor prognosis for the studied prostate cancer, as well as the possibility of targeted therapies based on the modulation of hypoxia, ROS, and the anti-cancer immune response.

Prostate cancer genetic background. The introduction of genetic testing in the determination of high-risk prostate cancer cases and selection of targeted chemotherapy in advanced prostate cancer patients

Introduction

Prostate cancer (PCa) is a major challenge in urology, with increasing incidence and mortality. Despite advances in diagnosis and treatment, certain patient groups remain poorly served. Genetic factors, particularly in hereditary prostate cancer (HPCa), are now recognized as significant contributors to disease progression. This review focuses on the role of genetic mutations in PCa, their impact on diagnosis, and management.

Material and methods

This review summarizes current literature on genetic mutations linked to PCa, including BRCA1, BRCA2, ATM, CHEK2, and others. These mutations are associated with more aggressive disease, earlier onset, and may influence treatment strategies. Guidelines from the Philadelphia Prostate Cancer Consensus Conference (PPCCC), the American National Comprehensive Cancer Network (NCCN), and the European Association of Urology (EAU) on genetic testing are also discussed.

Results

Genetic screening is increasingly recommended for high-risk individuals, such as those with a family history or aggressive PCa. Identifying mutations allows for early detection and tailored treatment, including more frequent screening and targeted therapies. Specific mutations, like those in BRCA genes, can benefit from chemotherapy in advanced stages. Genetic testing provides valuable information to guide patient management, improving early detection and patient outcomes.

Conclusions

Genetic testing plays a crucial role in PCa management, enabling personalized care for high-risk patients. As genetic research advances, incorporating genetic screening into clinical practice will enhance early diagnosis and treatment outcomes, ultimately improving patient survival and quality of life.

Genetic Analysis of Intraductal Carcinoma of the Prostate Detected in High-Grade Prostatic Intraepithelial Neoplasia Cases

Background The accurate diagnosis of intraductal carcinoma of the prostate (IDC-P) is occasionally challenging due to the similarity in pathological morphology between IDC-P and high-grade prostatic intraepithelial neoplasia (HGPIN). In this report, we reviewed the pathology of cases previously diagnosed as HGPIN to search for IDC-P cases effectively. In addition, we examined whether those cases had genetic abnormalities. Methods We reviewed 98 patients with HGPIN who underwent prostatectomy at our hospital between 2011 and 2021. They were reviewed by three pathologists to search for IDC-P findings by adding immunostaining for basement membrane markers. Genetic testing of prostatectomy specimens was performed to identify the presence of gene mutations. Results The typical IDC-P was diagnosed in two of the 98 patients. The Gleason score of background prostate cancer (PCa) was 4+5 and 4+4. Genetic testing revealed several mutations in DNA repair-related genes, such as CHEK2, FANCC, TOE1, RECQL, USG2A, and PRPF31. The pathological significance of these mutations has conflicting interpretations, as referenced in the ClinVar. Conclusions IDC-P cases can be identified from past HGPIN cases, and cases with genetic abnormalities of conflicting pathological significance can be efficiently detected. Accurate diagnosis of IDC-P enables early intervention with precision medicine for PCa. It is useful to pay attention to HGPIN cases to avoid missing true IDC-P.

Pharmacological treatment landscape of non-metastatic hormone-sensitive prostate cancer: A narrative review on behalf of the meet-URO Group

The definition of "non-metastatic hormone-sensitive prostate cancer" (nmHSPC) can be applied to patients with prostate cancer (PC) who are androgen-deprivation therapy-naïve and without evidence of metastatic disease. This definition includes heterogeneous situations; however, PC patients at high risk of metastatic spread - and who have not started a hormonal treatment - constitute a unique category with unmet clinical needs. This narrative review critically discusses the advances that characterize the rapidly evolving diagnostic and therapeutic scenario in the nmHSPC setting. We found that nmHSPC represents a grey zone in the context of PC. New clinical trials are trying to redefine the therapeutic algorithm of these patients, but escalating treatment seems not to be the right choice for the overall population. Biomarkers able to stratify patients - including molecular ones - are urgently needed, and biomarker-based clinical trials could clarify their prognostic and predictive role in the nmHSPC scenario.

CAP superfamily proteins in human: a new target for cancer therapy

The CAP (Cysteine-rich secretory protein, Antigen 5, and Pathogenesis-related protein 1) superfamily proteins (CAP proteins) are found in all kingdoms of life. The cysteine-rich secreted proteins are prevalent in human organs and tissues and serve as critical signaling molecules within cells, regulating a wide range of biochemical processes in the human body. Due to their involvement in numerous biological processes, CAP proteins have recently attracted significant attention, particularly in the context of tumorigenesis and cancer therapy. This review summarizes the expression patterns and roles of CAP proteins in various cancers. Additionally, it analyzes the mechanisms by which CAP proteins affect cancer cell proliferation and survival, regulate epithelial-mesenchymal transition, influence drug resistance, and regulate epigenetics. The review reveals that CAP proteins play distinct roles in various signaling pathways, such as the MAPK, PI3K-Akt, and p53 pathways, which are crucial for tumor progression. Furthermore, this review summarizes the tumor-inhibiting function of CAP proteins and their potential as cancer biomarkers. These findings suggest that CAP proteins represent a promising new target for innovative cancer diagnosis and treatment.

Comparison of Results from Two Commercially Available In-House Tissue-Based Comprehensive Genomic Profiling Solutions: Research Use Only AVENIO Tumor Tissue Comprehensive Genomic Profiling Kit and TruSight Oncology 500 Assay

Increased adoption of personalized medicine has brought comprehensive genomic profiling (CGP) to the forefront. However, differences in assay, bioinformatics, and reporting systems and lack of understanding of their complex interplay are a challenge for implementation and achieving uniformity in CGP testing. Two commercially available, tissue-based, in-house CGP assays were compared, in combination with a tertiary analysis solution in a research use only (RUO) context: the AVENIO Tumor Tissue CGP RUO Kit paired with navify Mutation Profiler (RUO) software and the TruSight Oncology 500 RUO assay paired with PierianDx Clinical Genomics Workspace software. Agreements and differences between the assays were assessed for short variants, copy number alterations, rearrangements, tumor mutational burden, and microsatellite instability, including variant categorization and clinical trial-matching (CTM) recommendations. Results showed good overall agreement for short variant, known gene fusion, and microsatellite instability detection. Important differences were obtained in tumor mutational burden scoring, copy number alteration detection, and CTM. Differences in variant and biomarker detection could be explained by bioinformatic approaches to variant calling, filtering, tiering, and normalization; differences in CTM, by underlying reported variants and conceptual differences in system parameters. Thus, distinctions between different approaches may lead to inconsistent results. Complexities in calling, filtering, and interpreting variants illustrate key considerations for implementation of any high-quality CGP in the laboratory and bringing uniformity to genomic insight results.

Extracellular RNAs from Whole Urine to Distinguish Prostate Cancer from Benign Prostatic Hyperplasia

RNAs, especially non-coding RNAs (ncRNAs), are crucial players in regulating cellular mechanisms due to their ability to interact with and regulate other molecules. Altered expression patterns of ncRNAs have been observed in prostate cancer (PCa), contributing to the disease's initiation, progression, and treatment response. This study aimed to evaluate the ability of a specific set of RNAs, including long ncRNAs (lncRNAs), microRNAs (miRNAs), and mRNAs, to discriminate between PCa and the non-neoplastic condition benign prostatic hyperplasia (BPH). After selecting by literature mining the most relevant RNAs differentially expressed in biofluids from PCa patients, we evaluated their discriminatory power in samples of unfiltered urine from 50 PCa and 50 BPH patients using both real-time PCR and droplet digital PCR (ddPCR). Additionally, we also optimized a protocol for urine sample manipulation and RNA extraction. This two-way validation study allowed us to establish that miRNAs (i.e., miR-27b-3p, miR-574-3p, miR-30a-5p, and miR-125b-5p) are more efficient biomarkers for PCa compared to long RNAs (mRNAs and lncRNAs) (e.g., PCA3, PCAT18, and KLK3), as their dysregulation was consistently reported in the whole urine of patients with PCa compared to those with BPH in a statistically significant manner regardless of the quantification methodology performed. Moreover, a significant increase in diagnostic performance was observed when molecular signatures composed of different miRNAs were considered. Hence, the abovementioned circulating ncRNAs represent excellent potential non-invasive biomarkers in urine capable of effectively distinguishing individuals with PCa from those with BPH, potentially reducing cancer overdiagnosis.

Structural basis of TMPRSS2 zymogen activation and recognition by the HKU1 seasonal coronavirus

The human seasonal coronavirus HKU1-CoV, which causes common colds worldwide, relies on the sequential binding to surface glycans and transmembrane serine protease 2 (TMPRSS2) for entry into target cells. TMPRSS2 is synthesized as a zymogen that undergoes autolytic activation to process its substrates. Several respiratory viruses, in particular coronaviruses, use TMPRSS2 for proteolytic priming of their surface spike protein to drive membrane fusion upon receptor binding. We describe the crystal structure of the HKU1-CoV receptor binding domain in complex with TMPRSS2, showing that it recognizes residues lining the catalytic groove. Combined mutagenesis of interface residues and comparison across species highlight positions 417 and 469 as determinants of HKU1-CoV host tropism. The structure of a receptor-blocking nanobody in complex with zymogen or activated TMPRSS2 further provides the structural basis of TMPRSS2 activating conformational change, which alters loops recognized by HKU1-CoV and dramatically increases binding affinity.

Impact of COVID-19 on sperm quality and the prostaglandin and polyamine systems in the seminal fluid

BACKGROUND

The implications of SARS-CoV-2 infection on male fertility remain largely unknown. Besides their well-known pro- and anti-inflammatory actions, prostaglandins and polyamines are present in semen, where they play key roles in sperm quality.

OBJECTIVES

To analyze semen parameters, oxidative profile and the seminal fluid prostaglandin and polyamine systems in samples collected from individuals without coronavirus disease 2019 diagnosis and men who recovered from coronavirus disease 2019.

MATERIALS AND METHODS

This study compared semen collected from men without positive coronavirus disease 2019 diagnosis with samples obtained from individuals 1-6 months and 7-30 months post SARS-CoV-2 infection. Semen parameters, thiobarbituric acid reactive substances, cyclooxygenase 2 expression by fluorescence immunocytochemistry and immunoblotting, prostaglandin levels by enzyme immunoassay, ornithine decarboxylase activity by a radioactive assay, and polyamine and acetylated polyamine levels by thin-layer chromatography were assessed.

RESULTS

In both groups of semen samples from coronavirus disease 2019 recovered men, sperm vitality, total and progressive sperm motility, and putrescine levels were significantly decreased when compared with samples from the uninfected group. In contrast, lipid peroxidation, leukocyte-associated cyclooxygenase 2 expression, and prostaglandin D2 levels were higher in semen from coronavirus disease 2019 recovered men than in samples from uninfected individuals. While sperm concentration and morphology, ornithine decarboxylase activity, and N-acetylputrescine levels were statistically diminished in semen obtained up to 6 months after coronavirus disease 2019 recovery, these parameters remained unchanged when samples were collected 7-30 months after coronavirus disease 2019 recovery. Coronavirus disease 2019 vaccination did not show negative effects on any of the parameters evaluated.

DISCUSSION AND CONCLUSION

Our work provides insights into the detrimental impact of coronavirus disease 2019 on several sperm parameters, in some cases, even more than a year after SARS-CoV-2 infection, which would be accompanied by alterations in the seminal fluid prostaglandin and polyamine profiles. Therefore, future treatments targeting the prostaglandin and polyamine pathways in coronavirus disease 2019 recovered men could lead to a successful reinstatement of semen parameters.

TNIK in disease: from molecular insights to therapeutic prospects

TRAF2 and NCK interacting kinase (TNIK), a critical interacting protein kinase, is currently receiving wide attention. TNIK is found in various human body organs and tissues and participates in cell motility, proliferation, and differentiation. On the one hand, its aberrant expression is related to the onset and progression of numerous malignant tumors. On the other hand, TNIK is important in neuronal growth, proliferation, differentiation, and synaptic formation. Thus, the novel therapeutic strategies for targeting TNIK offer a promising direction for cancer, neurological or psychotic disorders. Here, we briefly summarized the biological information of TNIK, reviewed the role and regulatory mechanism in cancer and neuropsychiatric diseases, and introduced the research progress of inhibitors targeting TNIK. Taken together, this review hopes to contribute to the in-depth understanding of the function and regulatory mechanism of TNIK, which is of great significance for revealing the role of TNIK in the occurrence and treatment of diseases.

Deep-Learning Model for Tumor-Type Prediction Using Targeted Clinical Genomic Sequencing Data

Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor-type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole-genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a data set of 39,787 solid tumors sequenced using a clinically targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivaling the performance of WGS-based methods. GDD-ENS can also guide diagnoses of rare type and cancers of unknown primary and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows could provide clinically relevant tumor-type predictions to guide treatment decisions in real time.

SIGNIFICANCE

We describe a highly accurate tumor-type prediction model, designed specifically for clinical implementation. Our model relies only on widely used cancer gene panel sequencing data, predicts across 38 distinct cancer types, and supports integration of patient-specific nongenomic information for enhanced decision support in challenging diagnostic situations. See related commentary by Garg, p. 906. This article is featured in Selected Articles from This Issue, p. 897.

The yin and yang of chromosomal instability in prostate cancer

Metastatic prostate cancer remains an incurable lethal disease. Studies indicate that prostate cancer accumulates genomic changes during disease progression and displays the highest levels of chromosomal instability (CIN) across all types of metastatic tumours. CIN, which refers to ongoing chromosomal DNA gain or loss during mitosis, and derived aneuploidy, are known to be associated with increased tumour heterogeneity, metastasis and therapy resistance in many tumour types. Paradoxically, high CIN levels are also proposed to be detrimental to tumour cell survival, suggesting that cancer cells must develop adaptive mechanisms to ensure their survival. In the context of prostate cancer, studies indicate that CIN has a key role in disease progression and might also offer a therapeutic vulnerability that can be pharmacologically targeted. Thus, a comprehensive evaluation of the causes and consequences of CIN in prostate cancer, its contribution to aggressive advanced disease and a better understanding of the acquired CIN tolerance mechanisms can translate into new tumour classifications, biomarker development and therapeutic strategies.

A cross-sectional study of ERG expression and the relationship with clinicopathological features of Prostate cancer in Southwestern Uganda

BACKGROUND

Prostate cancer is the leading cause of cancer-related death and the second most commonly diagnosed cancer among men in Uganda and most countries in Sub-Saharan Africa (SSA). The TMPRSS2-ERG fusion gene is the most common genetic alteration seen among prostate cancer patients. There are several contradicting reports about the association of ERG protein with poor prognosis, high PSA, and Gleason score. This study determined the prevalence of ERG expression and the relationship with PSA, Gleason score, and Age of prostate cancer patients in Southwestern Uganda.

METHODS

We reviewed 130 archived prostate biopsy (needle and TURP) specimens from patients of age ≥ 50 years who had a histological diagnosis of prostate cancer. We obtained their biodata, and preoperative PSA, from the archived records. We did Immunohistochemistry (IHC) to determine the prevalence of ERG expression.

RESULTS

The mean patient age in our study was 74.64 ± 10.19 years. Pre-operative PSA levels had been done for 79.2% of the participants. Most cancers (58.46%) were of high grade (grade group 3-5). ERG expression prevalence was 75.4% and its expression was independent of age, re-operative PSA, and Gleason score.

CONCLUSION

There is a significantly higher prevalence of ERG expression in our study compared to what is reported in other African-based studies. The expression of the ERG is independent of age, Gleason score, and serum PSA levels. A high proportion of our prostate cancer has high-grade disease at the time of diagnosis.

Unveiling the Genomic Landscape of Intraductal Carcinoma of the Prostate Using Spatial Gene Expression Analysis

Intraductal carcinoma of the prostate (IDCP) has recently attracted increasing interest owing to its unfavorable prognoses. To effectively identify the IDCP-specific gene expression profile, we took a novel approach of characterizing a typical IDCP case using spatial gene expression analysis. A formalin-fixed, paraffin-embedded sample was subjected to Visium CytAssist Spatial Gene Expression analysis. IDCP within invasive prostate cancer sites was recognized as a distinct cluster separate from other invasive cancer clusters. Highly expressed genes defining the IDCP cluster, such as MUC6, MYO16, NPY, and KLK12, reflected the aggressive nature of high-grade prostate cancer. IDCP sites also showed increased hypoxia markers HIF1A, BNIP3L, PDK1, and POGLUT1; decreased fibroblast markers COL1A2, DCN, and LUM; and decreased immune cell markers CCR5 and FCGR3A. Overall, these findings indicate that the hypoxic tumor microenvironment and reduced recruitment of fibroblasts and immune cells, which reflect morphological features of IDCP, may influence the aggressiveness of high-grade prostate cancer.

Multiplexed quantitative proteomics in prostate cancer biomarker development

Prostate cancer (PCa) is the most common non-skin cancer among men in the United States. However, the widely used protein biomarker in PCa, prostate-specific antigen (PSA), while useful for initial detection, its use alone cannot detect aggressive PCa and can lead to overtreatment. This chapter provides an overview of PCa protein biomarker development. It reviews the state-of-the-art liquid chromatography-mass spectrometry-based proteomics technologies for PCa biomarker development, such as enhancing the detection sensitivity of low-abundance proteins through antibody-based or antibody-independent protein/peptide enrichment, enriching post-translational modifications such as glycosylation as well as information-rich extracellular vesicles, and increasing accuracy and throughput using advanced data acquisition methodologies. This chapter also summarizes recent PCa biomarker validation studies that applied those techniques in diverse specimen types, including cell lines, tissues, proximal fluids, urine, and blood, developing novel protein biomarkers for various clinical applications, including early detection and diagnosis, prognosis, and therapeutic intervention of PCa.

Identification of gene fusions associated with amyotrophic lateral sclerosis

INTRODUCTION/AIMS

Genetics is an important risk factor for amyotrophic lateral sclerosis (ALS), a neurodegenerative disease affecting motor neurons. Recent findings demonstrate that in addition to specific genetic mutations, structural variants caused by genetic instability can also play a causative role in ALS. Genomic instability can lead to deletions, duplications, insertions, inversions, and translocations in the genome, and these changes can sometimes lead to fusion of distinct genes into a single transcript. Gene fusion events have been studied extensively in cancer; however, they have not been thoroughly investigated in ALS. The aim of this study was to determine whether gene fusions are present in ALS.

METHODS

Gene fusions were identified using STAR Fusion v1.10.0 software in bulk RNA-Seq data from human postmortem samples from publicly available data sets from Target ALS and the New York Genome Center ALS Consortium.

RESULTS

We report the presence of gene fusion events in several brain regions as well as in spinal cord samples in ALS. Although most gene fusions were intra-chromosomal events between neighboring genes and present in both ALS and control samples, there was a significantly greater number of unique gene fusions in ALS compared to controls. Lastly, we identified specific gene fusions with a significant burden in ALS, that were absent from both control samples and known cancer gene fusion databases.

DISCUSSION

Collectively, our findings reveal an enrichment of gene fusions in ALS and suggest that these events may be an additional genetic cause linked to ALS pathogenesis.

Ductal Adenocarcinoma of the Prostate with Novel Genetic Alterations Characterized by Next-Generation Sequencing

Ductal adenocarcinoma of the prostate (DAP) is an uncommon variant of prostate cancer associated with aggressive disease and poor outcome. It presents most frequently as a mixed tumor combined with acinar adenocarcinoma. Although the histopathological features of DAP are well known, its genomic characteristics are still evolving, prompting the suggestion that all DAP would benefit from molecular analysis with the purpose of improving tumor recognition, genetic classification, and, ultimately, personalized therapy. Herein, we report a case of DAP with novel genetic alterations (BCOR P1153S, ERG M219I, KDR A750E, POLE S1896P, and RAD21 T461del).

Recent advances in the investigation of fusion RNAs and their role in molecular pathology of cancer

Gene fusions have had a significant role in the development of various types of cancer, oftentimes involved in oncogenic activities through dysregulation of gene expression or signalling pathways. Some cancer-associated chromosomal translocations can undergo backsplicing, resulting in fusion-circular RNAs, a more stable isoform immune to RNase degradation. This stability makes fusion circular RNAs a promising diagnostic biomarker for cancer. While the detection of linear fusion RNAs and their function in certain cancers have been described in literature, fusion circular RNAs lag behind due to their low abundance in cancer cells. This review highlights current literature on the role of linear and circular fusion transcripts in cancer, tools currently available for detecting of these chimeric RNAs and their function and how they play a role in tumorigenesis.

Artificial intelligence applications in prostate cancer

Artificial intelligence (AI) applications have enabled remarkable advancements in healthcare delivery. These AI tools are often aimed to improve accuracy and efficiency of histopathology assessment and diagnostic imaging interpretation, risk stratification (i.e., prognostication), and prediction of therapeutic benefit for personalized treatment recommendations. To date, multiple AI algorithms have been explored for prostate cancer to address automation of clinical workflow, integration of data from multiple domains in the decision-making process, and the generation of diagnostic, prognostic, and predictive biomarkers. While many studies remain within the pre-clinical space or lack validation, the last few years have witnessed the emergence of robust AI-based biomarkers validated on thousands of patients, and the prospective deployment of clinically-integrated workflows for automated radiation therapy design. To advance the field forward, multi-institutional and multi-disciplinary collaborations are needed in order to prospectively implement interoperable and accountable AI technology routinely in clinic.

CTAT-LR-fusion: accurate fusion transcript identification from long and short read isoform sequencing at bulk or single cell resolution

Gene fusions are found as cancer drivers in diverse adult and pediatric cancers. Accurate detection of fusion transcripts is essential in cancer clinical diagnostics, prognostics, and for guiding therapeutic development. Most currently available methods for fusion transcript detection are compatible with Illumina RNA-seq involving highly accurate short read sequences. Recent advances in long read isoform sequencing enable the detection of fusion transcripts at unprecedented resolution in bulk and single cell samples. Here we developed a new computational tool CTAT-LR-fusion to detect fusion transcripts from long read RNA-seq with or without companion short reads, with applications to bulk or single cell transcriptomes. We demonstrate that CTAT-LR-fusion exceeds fusion detection accuracy of alternative methods as benchmarked with simulated and real long read RNA-seq. Using short and long read RNA-seq, we further apply CTAT-LR-fusion to bulk transcriptomes of nine tumor cell lines, and to tumor single cells derived from a melanoma sample and three metastatic high grade serous ovarian carcinoma samples. In both bulk and in single cell RNA-seq, long isoform reads yielded higher sensitivity for fusion detection than short reads with notable exceptions. By combining short and long reads in CTAT-LR-fusion, we are able to further maximize detection of fusion splicing isoforms and fusion-expressing tumor cells. CTAT-LR-fusion is available at https://github.com/TrinityCTAT/CTAT-LR-fusion/wiki.

The Inhibition of Serine Proteases by Serpins Is Augmented by Negatively Charged Heparin: A Concise Review of Some Clinically Relevant Interactions

Serine proteases are members of a large family of hydrolytic enzymes in which a particular serine residue in the active site performs an essential role as a nucleophile, which is required for their proteolytic cleavage function. The array of functions performed by serine proteases is vast and includes, among others, the following: (i) the ability to fight infections; (ii) the activation of blood coagulation or blood clot lysis systems; (iii) the activation of digestive enzymes; and (iv) reproduction. Serine protease activity is highly regulated by multiple families of protease inhibitors, known collectively as the SERine Protease INhibitor (SERPIN). The serpins use a conformational change mechanism to inhibit proteases in an irreversible way. The unusual conformational change required for serpin function provides an elegant opportunity for allosteric regulation by the binding of cofactors, of which the most well-studied is heparin. The goal of this review is to discuss some of the clinically relevant serine protease-serpin interactions that may be enhanced by heparin or other negatively charged polysaccharides. The paired serine protease-serpin in the framework of heparin that we review includes the following: thrombin-antithrombin III, plasmin-anti-plasmin, C1 esterase/kallikrein-C1 esterase inhibitor, and furin/TMPRSS2 (serine protease Transmembrane Protease 2)-alpha-1-antitrypsin, with the latter in the context of COVID-19 and prostate cancer.

Prostate cancer patient stratification by molecular signatures in the Veterans Precision Oncology Data Commons

Veterans are at an increased risk for prostate cancer, a disease with extraordinary clinical and molecular heterogeneity, compared with the general population. However, little is known about the underlying molecular heterogeneity within the veteran population and its impact on patient management and treatment. Using clinical and targeted tumor sequencing data from the National Veterans Affairs health system, we conducted a retrospective cohort study on 45 patients with advanced prostate cancer in the Veterans Precision Oncology Data Commons (VPODC), most of whom were metastatic castration-resistant. We characterized the mutational burden in this cohort and conducted unsupervised clustering analysis to stratify patients by molecular alterations. Veterans with prostate cancer exhibited a mutational landscape broadly similar to prior studies, including KMT2A and NOTCH1 mutations associated with neuroendocrine prostate cancer phenotype, previously reported to be enriched in veterans. We also identified several potential novel mutations in PTEN, MSH6, VHL, SMO, and ABL1 Hierarchical clustering analysis revealed two subgroups containing therapeutically targetable molecular features with novel mutational signatures distinct from those reported in the Catalogue of Somatic Mutations in Cancer database. The clustering approach presented in this study can potentially be used to clinically stratify patients based on their distinct mutational profiles and identify actionable somatic mutations for precision oncology.

Analysis of genetic biomarkers, polymorphisms in ADME-related genes and their impact on pharmacotherapy for prostate cancer

Prostate cancer (PCa) is a non-cutaneous malignancy in males with wide variation in incidence rates across the globe. It is the second most reported cause of cancer death. Its etiology may have been linked to genetic polymorphisms, which are not only dominating cause of malignancy casualties but also exerts significant effects on pharmacotherapy outcomes. Although many therapeutic options are available, but suitable candidates identified by useful biomarkers can exhibit maximum therapeutic efficacy. The single-nucleotide polymorphisms (SNPs) reported in androgen receptor signaling genes influence the effectiveness of androgen receptor pathway inhibitors and androgen deprivation therapy. Furthermore, SNPs located in genes involved in transport, drug metabolism, and efflux pumps also influence the efficacy of pharmacotherapy. Hence, SNPs biomarkers provide the basis for individualized pharmacotherapy. The pharmacotherapeutic options for PCa include hormonal therapy, chemotherapy (Docetaxel, Mitoxantrone, Cabazitaxel, and Estramustine, etc.), and radiotherapy. Here, we overview the impact of SNPs reported in various genes on the pharmacotherapy for PCa and evaluate current genetic biomarkers with an emphasis on early diagnosis and individualized treatment strategy in PCa.

Androgen Receptor Signaling in Prostate Cancer Genomic Subtypes

Prostate cancer (PCa) constitutes a significant cause of mortality, with over 37,000 new deaths each year [...].

Reduced PDE4D7 in prostate cancer correlates with genomic downregulation within the upstream PDE4D coding region

Aim

PDE4D7 expression is significantly associated with prostate cancer (PCa) progression, representing an attractive prognostic biomarker. We sought to determine whether other genes in the PDE4D coding region were associated.

Patients & methods

RNA from biopsy punch samples of resected tumor tissue was analyzed via RNA sequencing. RT-qPCR was used to determine PDE4D7 score.

Results

Numerous genomic sequences within the PDE4D coding region on Chr5q12 revealed similar mRNA expression profiles to PDE4D7. PART1 had a significantly similar expression pattern to PDE4D7 across samples, correlating with disease progression. However, many other genes also exhibited matched expression to PDE4D7, including miRNAs and lncRNAs.

Conclusion

These novel PDE4D7-associated genes, many of which are previously uncharacterized in cancer, represent putative PCa biomarkers and could have mechanistic roles in PCa progression.

Deep Learning Model for Tumor Type Prediction using Targeted Clinical Genomic Sequencing Data

Tumor type guides clinical treatment decisions in cancer, but histology-based diagnosis remains challenging. Genomic alterations are highly diagnostic of tumor type, and tumor type classifiers trained on genomic features have been explored, but the most accurate methods are not clinically feasible, relying on features derived from whole genome sequencing (WGS), or predicting across limited cancer types. We use genomic features from a dataset of 39,787 solid tumors sequenced using a clinical targeted cancer gene panel to develop Genome-Derived-Diagnosis Ensemble (GDD-ENS): a hyperparameter ensemble for classifying tumor type using deep neural networks. GDD-ENS achieves 93% accuracy for high-confidence predictions across 38 cancer types, rivalling performance of WGS-based methods. GDD-ENS can also guide diagnoses on rare type and cancers of unknown primary, and incorporate patient-specific clinical information for improved predictions. Overall, integrating GDD-ENS into prospective clinical sequencing workflows has enabled clinically-relevant tumor type predictions to guide treatment decisions in real time.

INTEGRATE-Circ and INTEGRATE-Vis: unbiased detection and visualization of fusion-derived circular RNA

MOTIVATION

Backsplicing of RNA results in circularized rather than linear transcripts, known as circular RNA (circRNA). A recently discovered and poorly understood subset of circRNAs that are composed of multiple genes, termed fusion-derived circular RNAs (fcircRNAs), represent a class of potential biomarkers shown to have oncogenic potential. Detection of fcircRNAs eludes existing analytical tools, making it difficult to more comprehensively assess their prevalence and function. Improved detection methods may lead to additional biological and clinical insights related to fcircRNAs.

RESULTS

We developed the first unbiased tool for detecting fcircRNAs (INTEGRATE-Circ) and visualizing fcircRNAs (INTEGRATE-Vis) from RNA-Seq data. We found that INTEGRATE-Circ was more sensitive, precise and accurate than other tools based on our analysis of simulated RNA-Seq data and our tool was able to outperform other tools in an analysis of public lymphoblast cell line data. Finally, we were able to validate in vitro three novel fcircRNAs detected by INTEGRATE-Circ in a well-characterized breast cancer cell line.

AVAILABILITY AND IMPLEMENTATION

Open source code for INTEGRATE-Circ and INTEGRATE-Vis is available at https://www.github.com/ChrisMaherLab/INTEGRATE-CIRC and https://www.github.com/ChrisMaherLab/INTEGRATE-Vis.

The screening, identification, design and clinical application of tumor-specific neoantigens for TCR-T cells

Recent advances in neoantigen research have accelerated the development of tumor immunotherapies, including adoptive cell therapies (ACTs), cancer vaccines and antibody-based therapies, particularly for solid tumors. With the development of next-generation sequencing and bioinformatics technology, the rapid identification and prediction of tumor-specific antigens (TSAs) has become possible. Compared with tumor-associated antigens (TAAs), highly immunogenic TSAs provide new targets for personalized tumor immunotherapy and can be used as prospective indicators for predicting tumor patient survival, prognosis, and immune checkpoint blockade response. Here, the identification and characterization of neoantigens and the clinical application of neoantigen-based TCR-T immunotherapy strategies are summarized, and the current status, inherent challenges, and clinical translational potential of these strategies are discussed.

Non-Coding RNAs: Foes or Friends for Targeting Tumor Microenvironment

Non-coding RNAs (ncRNAs) are a group of molecules critical for cell development and growth regulation. They are key regulators of important cellular pathways in the tumor microenvironment. To analyze ncRNAs in the tumor microenvironment, the use of RNA sequencing technology has revolutionized the field. The advancement of this technique has broadened our understanding of the molecular biology of cancer, presenting abundant possibilities for the exploration of novel biomarkers for cancer treatment. In this review, we will summarize recent achievements in understanding the complex role of ncRNA in the tumor microenvironment, we will report the latest studies on the tumor microenvironment using RNA sequencing, and we will discuss the potential use of ncRNAs as therapeutics for the treatment of cancer.

Prognostic value of E‑26 transformation‑specific‑related gene in prostate cancer based on immunohistochemistry analysis

E-26 transformation-specific-related gene (ERG) has been implicated in prostate cancer; however, its prognostic role remains unclear. Therefore, the present study aimed to investigate the association of ERG with the prognosis after radical prostatectomy in patients with prostate cancer. Patient data were collected at the Huadong Hospital, affiliated with Fudan University, between January 2016 and March 2020. ERG protein expression was detected using immunohistochemistry. Independent-sample t-tests and χ² tests were used to evaluate prostate cancer prognosis depending on ERG levels. The Kaplan-Meier method was used to estimate biochemical failure-free survival (BFFS) and the log-rank test was used to test the distribution. Prognostic factors were determined using Cox regression analysis. The median patient age was 69 years (range, 47-82 years). The median prostate-specific antigen (PSA) and free-PSA levels before treatment were 9.58 ng/ml (range, 0.003-187.400 ng/ml) and 1.13 ng/ml (range, 0.0059-30.6100 ng/ml), respectively. ERG protein expression was positive in 43 (16.6%) and negative in 216 (83.4%) cases. The median follow-up period and BFFS were 30 and 28 months, respectively. There was a significant difference in biochemical recurrence (P=0.017) between patients with positive and negative ERG expression. Patients with positive ERG expression had significantly worse BFFS curves compared with those with negative ERG expression (P=0.0038). In the multivariate Cox regression analysis, positive ERG expression was found to be an independent prognostic factor in patients with prostate cancer who underwent radical prostatectomy (hazard ratio, 4.08; 95% confidence interval, 2.03-8.17; P=0.000074). In conclusion, positive ERG expression is an independent prognostic risk factor for prostate cancer. These findings may be valuable for improvements in the clinical application of ERG immunohistochemistry.

Characterization and evaluation of gene fusions as a measure of genetic instability and disease prognosis in prostate cancer

BACKGROUND

Prostate cancer (PCa) is one of the most prevalent cancers worldwide. The clinical manifestations and molecular characteristics of PCa are highly variable. Aggressive types require radical treatment, whereas indolent ones may be suitable for active surveillance or organ-preserving focal therapies. Patient stratification by clinical or pathological risk categories still lacks sufficient precision. Incorporating molecular biomarkers, such as transcriptome-wide expression signatures, improves patient stratification but so far excludes chromosomal rearrangements. In this study, we investigated gene fusions in PCa, characterized potential novel candidates, and explored their role as prognostic markers for PCa progression.

METHODS

We analyzed 630 patients in four cohorts with varying traits regarding sequencing protocols, sample conservation, and PCa risk group. The datasets included transcriptome-wide expression and matched clinical follow-up data to detect and characterize gene fusions in PCa. With the fusion calling software Arriba, we computationally predicted gene fusions. Following detection, we annotated the gene fusions using published databases for gene fusions in cancer. To relate the occurrence of gene fusions to Gleason Grading Groups and disease prognosis, we performed survival analyses using the Kaplan-Meier estimator, log-rank test, and Cox regression.

RESULTS

Our analyses identified two potential novel gene fusions, MBTTPS2,L0XNC01::SMS and AMACR::AMACR. These fusions were detected in all four studied cohorts, providing compelling evidence for the validity of these fusions and their relevance in PCa. We also found that the number of gene fusions detected in a patient sample was significantly associated with the time to biochemical recurrence in two of the four cohorts (log-rank test, p-value < 0.05 for both cohorts). This was also confirmed after adjusting the prognostic model for Gleason Grading Groups (Cox regression, p-values < 0.05).

CONCLUSIONS

Our gene fusion characterization workflow revealed two potential novel fusions specific for PCa. We found evidence that the number of gene fusions was associated with the prognosis of PCa. However, as the quantitative correlations were only moderately strong, further validation and assessment of clinical value is required before potential application.

DNAfusion: an R/Bioconductor package for increased sensitivity of detecting gene fusions in liquid biopsies

BACKGROUND

EML4-ALK gene fusions are oncogenic drivers in non-small cell lung cancer (NSCLC), and liquid biopsies containing EML4-ALK fragments can be used to study tumor dynamics using next-generation sequencing (NGS). However, the sensitivity of EML4-ALK detection varies between pipelines and analysis tools.

RESULTS

We developed an R/Bioconductor package, DNAfusion, which can be applied to BAM files generated by commercially available NGS pipelines, such as AVENIO. Forty-eight blood samples from a training cohort consisting of 41 stage IV EML4-ALK-positive NSCLC patients and seven healthy controls were used to develop DNAfusion. DNAfusion detected EML4-ALK in significantly more samples (sensitivity = 61.0%) compared to AVENIO (sensitivity = 36.6%). The newly identified EML4-ALK-positive patients were verified using droplet digital PCR. DNAfusion was subsequently validated in a blinded validation cohort comprising 24 EML4-ALK-positive and 24 EML4-ALK-negative stage IV NSCLC patients. DNAfusion detected significantly more EML4-ALK individuals in the validation cohort (sensitivity = 62.5%) compared to AVENIO (sensitivity = 29.2%). DNAfusion demonstrated a specificity of 100% in both the training and validation cohorts.

CONCLUSION

Here we present DNAfusion, which increases the sensitivity of EML4-ALK detection in liquid biopsies and can be implemented downstream of commercially available NGS pipelines. The simplistic method of operating the R package makes it easy to implement in the clinical setting, enabling wider expansion of NGS-based diagnostics.

α-Mangostin Promotes In Vitro and In Vivo Degradation of Androgen Receptor and AR-V7 Splice Variant in Prostate Cancer Cells

A major limitation of current prostate cancer pharmacotherapy approaches is the inability of these compounds to target androgen receptor variants or mutants that develop during prostate cancer progression. The demand for novel therapeutics to prevent, slow, and treat prostate cancer is significant because FDA approved anti-androgens are associated with adverse events and can eventually drive drug-resistant prostate cancer. This study evaluated α-mangostin for its novel ability to degrade the androgen receptor and androgen receptor variants. α-Mangostin is one of more than 70 isoprenylated xanthones isolated from Garcinia mangostana that we have been evaluating for their anticancer potential. Prostate cancer cells treated with α-mangostin exhibited decreased levels of wild-type and mutated androgen receptors. Immunoblot, immunoprecipitation, and transfection experiments demonstrated that the androgen receptor was ubiquitinated and subsequently degraded via the proteasome, which we hypothesize occurs with the assistance of BiP, an ER chaperone protein that we have shown to associate with the androgen receptor. We also evaluated α-mangostin for its antitumor activity and promotion of androgen receptor degradation in vivo. In summary, our study demonstrates that androgen receptor degradation occurs through the novel activation of BiP and suggests a new therapeutic approach for prostate cancer.

Anti-HERV-K Drugs and Vaccines, Possible Therapies against Tumors

The footprint of human endogenous retroviruses (HERV), specifically HERV-K, has been found in malignancies, such as melanoma, teratocarcinoma, osteosarcoma, breast cancer, lymphoma, and ovary and prostate cancers. HERV-K is characterized as the most biologically active HERV due to possession of open reading frames (ORF) for all Gag, Pol, and Env genes, which enables it to be more infective and obstructive towards specific cell lines and other exogenous viruses, respectively. Some factors might contribute to carcinogenicity and at least one of them has been recognized in various tumors, including overexpression/methylation of long interspersed nuclear element 1 (LINE-1), HERV-K Gag, and Env genes themselves plus their transcripts and protein products, and HERV-K reverse transcriptase (RT). Therapies effective for HERV-K-associated tumors mostly target invasive autoimmune responses or growth of tumors through suppression of HERV-K Gag or Env protein and RT. To design new therapeutic options, more studies are needed to better understand whether HERV-K and its products (Gag/Env transcripts and HERV-K proteins/RT) are the initiators of tumor formation or just the disorder’s developers. Accordingly, this review aims to present evidence that highlights the association between HERV-K and tumorigenicity and introduces some of the available or potential therapies against HERV-K-induced tumors.

Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer

Current strategies for the clinical management of prostate cancer are inadequate for a precise risk stratification between indolent and aggressive tumors. Recently developed tissue-based molecular biomarkers have refined the risk assessment of the disease. The characterization of tissue biopsy components and subsequent identification of relevant tissue-based molecular alterations have the potential to improve the clinical decision making and patient outcomes. However, tissue biopsies are invasive and spatially restricted due to tumor heterogeneity. Therefore, there is an urgent need for complementary diagnostic and prognostic options. Liquid biopsy approaches are minimally invasive with potential utility for the early detection, risk stratification, and monitoring of tumors. In this review, we focus on tissue and liquid biopsy biomarkers for early diagnosis and risk stratification of prostate cancer, including modifications on the genomic, epigenomic, transcriptomic, and proteomic levels. High-risk molecular alterations combined with orthogonal clinical parameters can improve the identification of aggressive tumors and increase patient survival.

The impact of genetic aberrations on response to radium-223 treatment for castration-resistant prostate cancer with bone metastases

BACKGROUND

Radium (Ra)-223 is an established treatment option for patients with metastatic castrate-resistant prostate cancer (mCRPC) who have symptomatic bone metastases without soft tissue disease. Studies have indicated genetic aberrations that regulate DNA damage response (DDR) in prostate cancer can increase susceptibility to treatments such as poly ADP-ribose polymerase inhibitors and platinum-based therapies. This study aims to evaluate mCRPC response to Ra-223 stratified by tumor genomics.

METHODS

This is a retrospective study of mCRPC patients who received Ra-223 and genetic testing within the Mayo Clinic database (Arizona, Florida, and Minnesota) and Tulane Cancer Center. Patient demographics, genetic aberrations, treatment responses in terms of alkaline phosphatase (ALP) and prostate-specific antigen (PSA), and survival were assessed. Primary end points were ALP and PSA response. Secondary end points were progression-free survival (PFS) and overall survival (OS) from time of first radium treatment.

RESULTS

One hundred and twenty-seven mCRPC patients treated with Ra-223 had germline and/or somatic genetic sequencing. The median age at time of diagnosis and Ra-223 treatment was 61.0 and 68.6 years, respectively. Seventy-nine (62.2%) had Gleason score ≥ 8 at time of diagnosis. 50.4% received prior docetaxel, and 12.6% received prior cabazitaxel. Notable alterations include TP53 (51.7%), BRCA 1/2 (15.0%), PTEN (13.4%), ATM (11.7%), TMPRSS2-ERG (8.2%), RB deletion (3.4%), and CDK12 (1.9%). There was no significant difference in ALP or PSA response among the different genetic aberrations. Patients with a TMPRSS2-ERG mutation exhibited a trend toward lower OS 15.4 months (95% confidence interval [CI] 10.0-NR) versus 26.8 months (95% CI 20.9-35.1). Patients with an RB deletion had a lower PFS 6.0 months (95% CI 1.28-NR) versus 9.0 months (95% CI 7.3-11.1) and a lower OS 13.9 months (95% CI 5.2-NR) versus 26.5 months (95% CI 19.8-33.8).

CONCLUSIONS

Among mCRPC patients treated with Ra-223 at Mayo Clinic and Tulane Cancer Center, we did not find any clear negative predictors of biochemical response or survival to treatment. TMPRSS2-ERG and RB mutations were associated with a worse OS. Prospective studies and larger sample sizes are needed to determine the impact of genetic aberrations in response to Ra-223.

Mutator-Derived lncRNA Landscape: A Novel Insight Into the Genomic Instability of Prostate Cancer

Background

Increasing evidence has emerged to reveal the correlation between genomic instability and long non-coding RNAs (lncRNAs). The genomic instability-derived lncRNA landscape of prostate cancer (PCa) and its critical clinical implications remain to be understood.

Methods

Patients diagnosed with PCa were recruited from The Cancer Genome Atlas (TCGA) program. Genomic instability-associated lncRNAs were identified by a mutator hypothesis-originated calculative approach. A signature (GILncSig) was derived from genomic instability-associated lncRNAs to classify PCa patients into high-risk and low-risk groups. The biochemical recurrence (BCR) model of a genomic instability-derived lncRNA signature (GILncSig) was established by Cox regression and stratified analysis in the train set. Then its prognostic value and association with clinical features were verified by Kaplan–Meier (K-M) analysis and receiver operating characteristic (ROC) curve in the test set and the total patient set. The regulatory network of transcription factors (TFs) and lncRNAs was established to evaluate TF–lncRNA interactions.

Results

A total of 95 genomic instability-associated lncRNAs of PCa were identified. We constructed the GILncSig based on 10 lncRNAs with independent prognostic value. GILncSig separated patients into the high-risk (n = 121) group and the low-risk (n = 121) group in the train set. Patients with high GILncSig score suffered from more frequent BCR than those with low GILncSig score. The results were further validated in the test set, the whole TCGA cohort, and different subgroups stratified by age and Gleason score (GS). A high GILncSig risk score was significantly associated with a high mutation burden and a low critical gene expression (PTEN and CDK12) in PCa. The predictive performance of our BCR model based on GILncSig outperformed other existing BCR models of PCa based on lncRNAs. The GILncSig also showed a remarkable ability to predict BCR in the subgroup of patients with TP53 mutation or wild type. Transcription factors, such as FOXA1, JUND, and SRF, were found to participate in the regulation of lncRNAs with prognostic value.

Conclusion

In summary, we developed a prognostic signature of BCR based on genomic instability-associated lncRNAs for PCa, which may provide new insights into the epigenetic mechanism of BCR.

Identification, virtual screening and molecular dynamic analysis of novel TMPRSS2 inhibitors from natural compound database as potential entry-blocking agents in SARS-CoV-2 therapy

Scientific insights gained from the severe acute respiratory syndrome (SARS) and middle east respiratory syndrome (MERS) outbreaks have been assisting scientists and researchers in the quest of antiviral drug discovery process against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronaviruses and influenza viruses both rely on the host type 2 transmembrane serine protease, TMPRSS2, for entry and propagation. Recent studies report SARS-CoV-2 also uses TMPRSS2 to enter cells. In the current study, we employed structure-based virtual screening of 1,82,651 natural compounds downloaded from the zin database against the homology model of the TMPRSS2 protein, followed by a molecular dynamics-based simulation to identify potential TMPRSS2 hits. The virtual screening yielded 110 hits with docking scores ranging from -8.654 to -6.775 and glide energies ranging from -55.714 to -29.065 kcal/mol. The binding mode analysis revealed that the hit molecules made H-bond, Pi-Pi stacking and salt bridge contacts with the TMPRSS2 active site residues. MD simulations of the top two hits (ZINC000095912839 and ZINC000085597504) revealed to form a stable complex with TMPRSS2, with a minimal RMSD and RMSF fluctuation. Both the hit structures interacted strongly with the Asp180, Gln183, Gly184, Ser186, Gly207 and Gly209, as predicted by Glide XP docking, and formed a significant H-bond interaction with Ser181 in MD simulation. Among these two, ZINC000095912839 was having the most stable binding interaction with TMPRSS2 of the two molecules. The present study successfully identified TMPRSS2 ligands from a database of zinc natural molecules as potential leads for novel SARs-CoV-2 treatment.

SUPPLEMENTARY INFORM

The online version contains supplementary material available at 10.1007/s11224-022-01991-3.

Fusion Genes in Prostate Cancer: A Comparison in Men of African and European Descent

Simple Summary

Men of African origin have a 2–3 times greater chance of developing prostate cancer than those of European origin, and of patients that are diagnosed with the disease, men of African descent are 2 times more likely to die compared to white men. Men of African origin are still greatly underrepresented in genetic studies and clinical trials. This, unfortunately, means that new discoveries in cancer treatment are missing key information on the group with a greater chance of mortality. A fusion gene is a hybrid gene formed from two previously independent genes. Fusion genes have been found to be common in all main types of human cancer. The objective of this study was to increase our knowledge of fusion genes in prostate cancer using computational approaches and to compare fusion genes between men of African and European origin. This identified novel gene fusions unique to men of African origin and suggested that this group has a greater number of fusion genes.

Abstract

Prostate cancer is one of the most prevalent cancers worldwide, particularly affecting men living a western lifestyle and of African descent, suggesting risk factors that are genetic, environmental, and socioeconomic in nature. In the USA, African American (AA) men are disproportionately affected, on average suffering from a higher grade of the disease and at a younger age compared to men of European descent (EA). Fusion genes are chimeric products formed by the merging of two separate genes occurring as a result of chromosomal structural changes, for example, inversion or trans/cis-splicing of neighboring genes. They are known drivers of cancer and have been identified in 20% of cancers. Improvements in genomics technologies such as RNA-sequencing coupled with better algorithms for prediction of fusion genes has added to our knowledge of specific gene fusions in cancers. At present AA are underrepresented in genomic studies of prostate cancer. The primary goal of this study was to examine molecular differences in predicted fusion genes in a cohort of AA and EA men in the context of prostate cancer using computational approaches. RNA was purified from prostate tissue specimens obtained at surgery from subjects enrolled in the study. Fusion gene predictions were performed using four different fusion gene detection programs. This identified novel putative gene fusions unique to AA and suggested that the fusion gene burden was higher in AA compared to EA men.

Identification of novel TMPRSS2 inhibitors against SARS-CoV-2 infection: a structure-based virtual screening and molecular dynamics study

The scientific insights gained from the severe acute respiratory syndrome (SARS) and the middle east respiratory syndrome (MERS) outbreaks are helping scientists to fast-track the antiviral drug discovery process against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Coronaviruses, as well as influenza viruses, depend on host type 2 transmembrane serine protease, TMPRSS2, for entry and propagation in the human cell. Recent studies show that SARS-CoV-2 also uses TMPRSS2 for its cell entry. In the present study, a structure-based virtual screening of 52,337, protease ligands downloaded from the Zinc database was carried out against the homology model of TMPRSS2 protein followed by the molecular dynamics-based simulation to identify potential TMPRSS2 hits. The virtual screening has identified 13 hits with a docking score range of -10.447 to -9.863 and glide energy range of -60.737 to -40.479 kcal/mol. The binding mode analysis shows that the hit molecules form H-bond (Asp180, Gly184 & Gly209), Pi-Pi stacking (His41), and salt bridge (Asp180) type of contacts with the active site residues of TMPRSS2. In the MD simulation of ZINC000013444414, ZINC000137976768, and ZINC000143375720 hits show that these molecules form a stable complex with TMPRSS2. The complex equilibrates well with a minimal RMSD and RMSF fluctuation. All three structures, as predicted in Glide XP docking, show a prominent interaction with the Asp180, Gly184, Gly209, and His41. Further, MD simulation also identifies a notable H-bond interaction with Ser181 for all three hits. Among these hits, ZINC000143375720 shows the most stable binding interaction with TMPRSS2. The present study is successful in identifying TMPRSS2 ligands from zinc data base for a possible application in the treatment of COVID-19.

Molecular mechanisms and genetic alterations in prostate cancer: From diagnosis to targeted therapy

Prostate cancer remains one of the most lethal malignancies among men worldwide. Although the primary tumor can be successfully managed by surgery and radiotherapy, advanced metastatic carcinoma requires better therapeutic approaches. In this context, a deeper understanding of the molecular mechanisms that underlie the initiation and progression of this disease is urgently needed, leading to the identification of new diagnostic/prognostic markers and the development of more effective treatments. Herein, the current state of knowledge of prostate cancer genetic alterations is discussed, with a focus on their potential in tumor detection and staging as well as in the screening of novel therapeutics.

Androgen Receptor-Mediated Transcription in Prostate Cancer

Androgen receptor (AR)-mediated transcription is critical in almost all stages of prostate cancer (PCa) growth and differentiation. This process involves a complex interplay of coregulatory proteins, chromatin remodeling complexes, and other transcription factors that work with AR at cis-regulatory enhancer regions to induce the spatiotemporal transcription of target genes. This enhancer-driven mechanism is remarkably dynamic and undergoes significant alterations during PCa progression. In this review, we discuss the AR mechanism of action in PCa with a focus on how cis-regulatory elements modulate gene expression. We explore emerging evidence of genetic variants that can impact AR regulatory regions and alter gene transcription in PCa. Finally, we highlight several outstanding questions and discuss potential mechanisms of this critical transcription factor.

SPINKs in Tumors: Potential Therapeutic Targets

The serine protease inhibitor Kazal type (SPINK) family includes SPINK1-14 and is the largest branch in the serine protease inhibitor family. SPINKs play an important role in pancreatic physiology and disease, sperm maturation and capacitation, Nager syndrome, inflammation and the skin barrier. Evidence shows that the unregulated expression of SPINK1, 2, 4, 5, 6, 7, and 13 is closely related to human tumors. Different SPINKs exhibit various regulatory modes in different tumors and can be used as tumor prognostic markers. This article reviews the role of SPINK1, 2, 4, 5, 6, 7, and 13 in different human cancer processes and helps to identify new cancer treatment targets.

Investigating the Role of Obesity in Prostate Cancer and Identifying Biomarkers for Drug Discovery: Systems Biology and Deep Learning Approaches

Prostate cancer (PCa) is the second most frequently diagnosed cancer for men and is viewed as the fifth leading cause of death worldwide. The body mass index (BMI) is taken as a vital criterion to elucidate the association between obesity and PCa. In this study, systematic methods are employed to investigate how obesity influences the noncutaneous malignancies of PCa. By comparing the core signaling pathways of lean and obese patients with PCa, we are able to investigate the relationships between obesity and pathogenic mechanisms and identify significant biomarkers as drug targets for drug discovery. Regarding drug design specifications, we take drug–target interaction, drug regulation ability, and drug toxicity into account. One deep neural network (DNN)-based drug–target interaction (DTI) model is trained in advance for predicting drug candidates based on the identified biomarkers. In terms of the application of the DNN-based DTI model and the consideration of drug design specifications, we suggest two potential multiple-molecule drugs to prevent PCa (covering lean and obese PCa) and obesity-specific PCa, respectively. The proposed multiple-molecule drugs (apigenin, digoxin, and orlistat) not only help to prevent PCa, suppressing malignant metastasis, but also result in lower production of fatty acids and cholesterol, especially for obesity-specific PCa.

Long Non-coding RNAs LINC01679 as a Competitive Endogenous RNAs Inhibits the Development and Progression of Prostate Cancer via Regulating the miR-3150a-3p/SLC17A9 Axis

Long non-coding RNAs (lncRNAs) have been indicated as the candidate factors to predict cancer prognosis. However, it is still unknown whether lncRNA combinations may be utilized for predicting overall survival (OS) of prostate cancer (PCa). The present work focused on selecting the potent OS-related lncRNA signature for PCa and studying its molecular mechanism to enhance the prognosis prediction accuracy. Differentially expressed lncRNAs (DElncRNAs) or differentially expressed genes (DEGs) were obtained based on TCGA database by R software “edgeR” package. lncRNAs or mRNAs significantly related to PCa were screened through univariate as well as multivariate Cox regression, for the construction of the risk model for prognosis prediction. Moreover, this constructed risk model was validated through ROC analysis, univariate regression, and Kaplan–Meier (KM) analysis. Additionally, we built a lncRNA–miRNA–mRNA ceRNA network through bioinformatics analysis. Colony formation, CCK-8, flow cytometry, scratch, and Transwell assays were performed based on PCa cells subjected to small interfering RNA (siRNA) targeting LINC01679/SLC17A9 and vector expressing LINC01679/SLC17A9 transfection. Thereafter, the ceRNA mechanism was clarified via qRT-PCR, Western blotting (WB), RNA pull-down, and luciferase reporter assays. Nude mouse tumor xenograft was established to examine LINC01679’s oncogenicity within PCa cells. According to our results, LINC01679 depletion promoted cell proliferation, metastasis, tumor growth, and inhibited cell apoptosis in vivo and in vitro, which was also associated with poor survival. LINC01679 regulated miR-3150a-3p level by sponging it. Importantly, miR-3150a-3p overexpression was related to the increased proliferation and decreased apoptosis of PCa cells. Rescue assays suggested that miR-3150a-3p mimics rescued the repression on PCa progression mediated by LINC01679 upregulation, but SLC17A9 downregulation reversed the miR-3150a-3p inhibitor-mediated repression on PC progression. Importantly, SLC17A9 downregulation rescued the repression on PCa progression mediated by LINC01679 upregulation. LINC01679 and SLC17A9 are tightly associated with certain clinicopathological characteristics of PCa and its prognostic outcome. In addition, LINC01679 is the ceRNA that suppresses PCa development through modulating the miR-3150a-3p/SLC17A9 axis.