Copy number alteration burden predicts prostate cancer relapse

The Germline and Somatic Origins of Prostate Cancer Heterogeneity

SIGNIFICANCE

This study uncovered 223 recurrently mutated driver regions using the largest cohort of prostate tumors to date. It reveals associations between germline SNPs, somatic drivers, and tumor aggression, offering significant insights into how prostate tumor evolution is shaped by germline factors and the timing of somatic mutations.

Characterization of the Biochemical Recurrence Prediction Ability and Progression Correlation of Peroxiredoxins Family in Prostate Cancer Based on Integrating Single-Cell RNA-Seq and Bulk RNA-Seq Cohorts

INTRODUCTION

The peroxiredoxins (PRDXs) family plays a crucial role in balancing reactive oxygen species (ROS) levels in tumor cells. However, its potential role in prognosis and therapy response of prostate cancer (PCa) remains unknown.

METHODS

In this study, we utilized 2 public single-cell RNA datasets and 8 bulk-RNA datasets to investigate the clinical value of six PRDXs family members in PCa. Expression comparison, biochemical recurrence analysis, and therapy response analysis were measured. Pathway enrichments were utilized to predict the potential down-stream pathway it may involve. In vitro experiments were used to validate the function of PRDX5 in the progression of castration-resistant prostate cancer (CRPC) cell lines.

RESULT

Among the PRDXs family, PRDX5 was most related to the advancement of prostate cancer. A nomogram integrating the expression of PRDX5 with clinical features was developed to better predict clinical outcomes in PCa patients compared to 30 published signatures. Immunohistochemistry was used to verify that PRDX5 expression was higher in advanced levels of PCa tissue. Gene Set Enrichment Analysis (GSEA) and pathway predictive analysis revealed that the PRDX5 related genes were mainly relevant to ROS Pathway, Mitochondria-related functions, cellular respiration, and oxidative phosphorylation. In vitro cell proliferation assays, ROS determination assay, and apoptosis assay together revealed that depletion of PRDX5 induces apoptosis via ROS accumulation in CRPC cells. Moreover, the expression of PRDX5 in CRPC cells also affects the sensitivity to the ARSI therapy.

CONCLUSION

This study offers new evidence for determining that the expression of PRDX5 is associated with advanced tumor grade, poor prognosis, and suboptimal response to multiple therapies in PCa within the PRDXs family. Last but not least, our study provides new insights into precision medicine in PCa and provides a reference for further research on PRDX5.

The Landscape of Prostate Tumour Methylation

Prostate cancer is characterized by profound clinical and molecular heterogeneity. While its genomic heterogeneity is well-characterized, its epigenomic heterogeneity remains less understood. We therefore created a compendium of 3,001 multi-ancestry prostate methylomes spanning normal tissue through localized disease of all grades to poly-metastatic disease. A subset of 884 samples had multi-omic DNA and/or RNA characterization. We identify four epigenomic subtypes that risk-stratify patients and reflect distinct evolutionary trajectories. We demonstrate extensive regulatory interplay between DNA ploidy and DNA methylation, with transcriptional consequences that vary across genes and disease stages. We define the epigenetic dysregulation signatures of the 15 most important clinico-molecular features, creating predictive models for each. For example, we identify specific epigenetic features that predict patient outcome and that are synergistic with clinico-genomic prognostic features. These results define a complex interplay between tumour genetics and epigenetics that converges to modify gene-expression programs and clinical presentation.

Genomic instability is associated with response to [¹⁷⁷Lu]Lu-PSMA-I&T radioligand therapy: an exploratory, preliminary liquid biopsy analysis

BACKGROUND

PSMA-targeted radioligand therapies (PSMA RLT) are an effective and safe option for metastatic castration-resistant prostate cancer, but responsive subtypes and their biomarkers are not fully defined.

METHODS

Plasma samples for cell-free DNA (cfDNA) analysis were collected from 17 patients undergoing [¹⁷⁷Lu]Lu-PSMA-I&T. CfDNA underwent whole-genome sequencing to establish copy number variation (CNV) profiles and circulating-tumor DNA (ctDNA) levels and compared between prostate-specific antigen (PSA) response- and 1-year overall survival (1YOS) groups.

RESULTS

Non-responders exhibited higher degrees of cfDNA CNV burden (P = 0.048) and higher ctDNA levels (P = 0.036) than responders. Both markers allowed for the differentiation of responses (AUC: 0.792, 0.806) and 1YOS (AUC: 0.778, 0.847).

CONCLUSION

Unresponsive patients exhibited higher levels of cfDNA genomic instability and ctDNA levels, warranting genome-wide CNV profiling studies next to targeted approaches for mechanistic radiobiological insights and their value as response biomarkers for PSMA RLTs.

Key considerations for a prostate cancer mRNA vaccine

Prostate cancer has the second highest cancer mortality rate in the UK in males. Early prostate cancer is typically asymptomatic, with diagnosis at a locally advanced or metastatic stage. In addition, the inherent heterogeneity of prostate cancer tumours differs significantly in terms of genetic, molecular, and histological features. The successful treatment of prostate cancer is therefore exceedingly challenging. Immunotherapies, particularly therapeutic vaccines, have been widely used in preclinical and clinical studies to treat various cancers. Sipuleucel-T was the first cancer vaccine approved by the FDA for the treatment of asymptomatic or minimally symptomatic metastatic castration-resistant prostate cancer (mCRPC), ushering in a new era of immunotherapy. In this review, the latest immunotherapy strategies for prostate cancer are considered with key tumour-associated antigens (TAA) and tumour-specific antigens (TSA) highlighted. The key components of mRNA vaccines include in vitro transcription, stability, and immunogenicity. Finally, strategies to circumvent in vivo mRNA degradation and approaches to optimise in vitro transcription (IVT) process are also discussed.

The landscape of N6-methyladenosine in localized primary prostate cancer

N6-methyladenosine (m6A), the most abundant internal RNA modification in humans, regulates most aspects of RNA processing. Prostate cancer is characterized by widespread transcriptomic dysregulation; therefore, we characterized the m6A landscape of 162 localized prostate tumors with matched DNA, RNA and protein profiling. m6A abundance varied dramatically across tumors, with global patterns emerging via complex germline-somatic cooperative regulation. Individual germline polymorphisms regulated m6A abundance, cooperating with somatic mutation of cancer driver genes and m6A regulators. The resulting complex patterns were associated with prognostic clinical features and established the biomarker potential of global and locus-specific m6A patterns. Tumor hypoxia dysregulates m6A profiles, bridging prior genomic and proteomic observations. Specific m6A sites, such as those in VCAN, drive disease aggression, associating with poor outcomes, tumor growth and metastasis. m6A dysregulation is thus associated with key events in the natural history of prostate cancer: germline risk, microenvironmental dysregulation, somatic mutation and metastasis.

Dual inhibition of ATR and DNA-PKcs radiosensitizes ATM-mutant prostate cancer

In advanced castration resistant prostate cancer (CRPC), mutations in the DNA damage response (DDR) gene ataxia telangiectasia mutated (ATM) are common. While poly(ADP-ribose) polymerase inhibitors are approved in this context, their clinical efficacy remains limited. Thus, there is a compelling need to identify alternative therapeutic avenues for ATM mutant prostate cancer patients. Here, we generated matched ATM-proficient and ATM-deficient CRPC lines to elucidate the impact of ATM loss on DDR in response to DNA damage via irradiation. Through unbiased phosphoproteomic screening, we unveiled that ATM-deficient CRPC lines maintain dependence on downstream ATM targets through activation of ATR and DNA-PKcs kinases. Dual inhibition of ATR and DNA-PKcs effectively inhibited downstream γH2AX foci formation in response to irradiation and radiosensitized ATM-deficient lines to a greater extent than either ATM-proficient controls or single drug treatment. Further, dual inhibition abrogated residual downstream ATM pathway signaling and impaired replication fork dynamics. To circumvent potential toxicity, we leveraged the RUVBL1/2 ATPase inhibitor Compound B, which leads to the degradation of both ATR and DNA-PKcs kinases. Compound B effectively radiosensitized ATM-deficient CRPC in vitro and in vivo, and impacted replication fork dynamics. Overall, dual targeting of both ATR and DNA-PKcs is necessary to block DDR in ATM-deficient CRPC, and Compound B could be utilized as a novel therapy in combination with irradiation in these patients.

Causes of evolutionary divergence in prostate cancer

Cancer progression involves the sequential accumulation of genetic alterations that cumulatively shape the tumour phenotype. In prostate cancer, tumours can follow divergent evolutionary trajectories that lead to distinct subtypes, but the causes of this divergence remain unclear. While causal inference could elucidate the factors involved, conventional methods are unsuitable due to the possibility of unobserved confounders and ambiguity in the direction of causality. Here, we propose a method that circumvents these issues and apply it to genomic data from 829 prostate cancer patients. We identify several genetic alterations that drive divergence as well as others that prevent this transition, locking tumours into one trajectory. Further analysis reveals that these genetic alterations may cause each other, implying a positive-feedback loop that accelerates divergence. Our findings provide insights into how cancer subtypes emerge and offer a foundation for genomic surveillance strategies aimed at monitoring the progression of prostate cancer.

Tumour hypoxia in driving genomic instability and tumour evolution

Intratumour hypoxia is a feature of all heterogenous solid tumours. Increased levels or subregions of tumour hypoxia are associated with an adverse clinical prognosis, particularly when this co-occurs with genomic instability. Experimental evidence points to the acquisition of DNA and chromosomal alterations in proliferating hypoxic cells secondary to inhibition of DNA repair pathways such as homologous recombination, base excision repair and mismatch repair. Cell adaptation and selection in repair-deficient cells give rise to a model whereby novel single-nucleotide mutations, structural variants and copy number alterations coexist with altered mitotic control to drive chromosomal instability and aneuploidy. Whole-genome sequencing studies support the concept that hypoxia is a critical microenvironmental cofactor alongside the driver mutations in MYC, BCL2, TP53 and PTEN in determining clonal and subclonal evolution in multiple tumour types. We propose that the hypoxic tumour microenvironment selects for unstable tumour clones which survive, propagate and metastasize under reduced immune surveillance. These aggressive features of hypoxic tumour cells underpin resistance to local and systemic therapies and unfavourable outcomes for patients with cancer. Possible ways to counter the effects of hypoxia to block tumour evolution and improve treatment outcomes are described.

Exploring Mechanisms and Biomarkers of Breast Cancer Invasion and Migration: An Explainable Gene-Pathway-Compounds Neural Network

BACKGROUNDS

Exploring the molecular features that drive breast cancer invasion and migration remains an important biological and clinical challenge. In recent years, the use of interpretable machine learning models has enhanced our understanding of the underlying mechanisms of disease progression.

METHODS

In this study, we present a novel gene-pathway-compound-related sparse deep neural network (GPC-Net) for investigating breast cancer invasion and migration. The GPC-Net is an interpretable neural network model that utilizes molecular data to predict cancer status. It visually represents genes, pathways, and associated compounds involved in these pathways.

RESULTS

Compared with other modeling methods, GPC-Net demonstrates superior performance. Our research identifies key genes, such as ADCY8, associated with invasive breast cancer and verifies their expression in breast cancer cells. In addition, we conducted a preliminary exploration of several pathways.

CONCLUSION

GPC-Net is among the pioneering deep neural networks that incorporate pathways and compounds, aiming to balance interpretability and performance. It is expected to offer a more convenient approach for future biomedical research.

Molecular Landscape of Aggressive Histologic Subtypes of Localized Prostate Cancer

Despite incredible progress in describing the molecular underpinnings of prostate cancer over the last decades, pathologic examination remains indispensable for predicting aggressive behavior in the localized setting. Beyond pathologic grade, specific histologic findings have emerged as critical prognostic or predictive indicators. Here, the authors review molecular correlates of aggressive histologic subtypes of prostate cancer in the localized setting, demonstrating that many of the signature molecular alterations found in metastatic disease-such as tumor suppressor gene loss and DNA repair defects-are enriched in primary disease with adverse histologic features, presaging aggressive behavior, and presenting opportunities for earlier germline screening or targeted therapies.

Unveiling Racial Disparities in Localized Prostate Cancer: A Systems-Level Exploration of the lncRNA Landscape

BACKGROUND/OBJECTIVES

Prostate cancer (PC) is the most common non-cutaneous cancer in men globally, and one which displays significant racial disparities. Men of African descent (AF) are more likely to develop PC and face higher mortality compared to men of European descent (EU). The biological mechanisms underlying these differences remain unclear. Long non-coding RNAs (lncRNAs), recognized as key regulators of gene expression and immune processes, have emerged as potential contributors to these disparities. This study aimed to investigate the regulatory role of lncRNAs in localized PC in AF men relative to those of EU and assess their involvement in immune response and inflammation.

METHODS

A systems biology approach was employed to analyze differentially expressed (DE) lncRNAs and their roles in prostate cancer (PC). Immune-related pathways were investigated through over-representation analysis of lncRNA-mRNA networks. The study also examined the effects of vitamin D supplementation on lncRNA expression in African descent (AF) PC patients, highlighting their potential regulatory roles in immune response and inflammation.

RESULTS

Key lncRNAs specific to AF men were identified, with several being implicated for immune response and inflammatory processes. Notably, 10 out of the top 11 ranked lncRNAs demonstrated strong interactions with immune-related genes. Pathway analysis revealed their regulatory influence on antigen processing and presentation, chemokine signaling, and ribosome pathways, suggesting their critical roles in immune regulation.

CONCLUSIONS

These findings highlight the pivotal role of lncRNAs in PC racial disparities, particularly through immune modulation. The identified lncRNAs may serve as potential biomarkers or therapeutic targets to address racial disparities in PC outcomes.

Molecular subtyping combined with multiomics analysis to study correlation between TACE refractoriness and tumor stemness in hepatocellular carcinoma

BACKGROUND

Transarterial chemoembolization (TACE) refractoriness is a significant challenge in treating intermediate to advanced-stage hepatocellular carcinoma (HCC). A few studies suggest that liver cancer stem cells (LCSCs) may be associated with TACE refractoriness. This study aims to explore the potential correlation between TACE refractoriness and HCC stemness, highlighting its clinical significance.

METHODS

This research encompassed the analysis of diverse HCC datasets, including RNA-sequencing, microarray, single-cell RNA-sequencing, and clinical cohorts. We identified common genes between TACE refractoriness and tumor stemness (TSGs). Unsupervised clustering was employed to classify HCC patients into different clusters based on TSGs (TRS clusters). The study explored the differences in clinical prognosis, biological characteristics, genomic variations, immune landscapes, and treatment responses among the TRS clusters.

RESULTS

Patients with TACE-refractoriness demonstrated significantly higher tumor stemness. Our study identified 33 TSGs and established two TRS clusters, including C1 and C2. C1 was associated with TACE refractoriness, elevated tumor stemness, and poorer prognosis. Genomic alterations were found to be significantly different between the TRS clusters. The C1 exhibited signs of immunosuppression and lower activity of immune effector cells, while the C2 had a more robust immune response and higher level of immune cell presence. Single-cell RNA-seq revealed distinct cell type characteristics in each subtypes, with the C1 showing a higher proportion of stem cells and malignant cells.

CONCLUSION

Our findings establish a connection between TACE refractoriness and tumor stemness in HCC, proposing a novel subtype classification to guide personalized treatment. Insights gained may facilitate overcoming TACE refractoriness and the development of innovative therapies.

The Emerging Predictive and Prognostic Role of Aggressive-Variant-Associated Tumor Suppressor Genes Across Prostate Cancer Stages

Aggressive variant prostate cancer (AVPC) is characterized by a molecular signature involving combined defects in TP53, RB1, and/or PTEN (AVPC-TSGs), identifiable through immunohistochemistry or genomic analysis. The reported prevalence of AVPC-TSG alterations varies widely, reflecting differences in assay sensitivity, treatment pressure, and disease stage evolution. Although robust clinical evidence is still emerging, the study of AVPC-TSG alterations in prostate cancer (PCa) is promising. Alterations in TP53, RB1, and PTEN, as well as the combined loss of AVPC-TSGs, may have significant implications for prognosis and treatment. These biomarkers might help predict responses to various therapies, including hormonal treatments, cytotoxic agents, radiotherapy, and targeted therapies. Understanding the impact of these molecular alterations in patients with PCa is crucial for personalized management. In this review, we provide a comprehensive overview of the emerging prognostic and predictive roles of AVPC-TSG alterations across PCa stages. Moreover, we discuss the implications of different methods used for detecting AVPC-TSG alterations and summarize factors influencing their prevalence. As our comprehension of the genomic landscape of PCa disease deepens, incorporating genomic profiling into clinical decision making will become increasingly important for improving patient outcomes.

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.

Colibactin Exerts Androgen-dependent and -independent Effects on Prostate Cancer

BACKGROUND AND OBJECTIVE

The etiology of prostate cancer (PC) is multifactorial and poorly understood. It has been suggested that colibactin-producing Escherichia coli positive for the pathogenicity island pks (pks+) initiate cancers via induction of genomic instability. In PC, androgens promote oncogenic translocations. Our aim was to investigate the association of pks+E. coli with PC diagnosis and molecular architecture, and its relationship with androgens.

METHODS

We quantified the association of pks+E. coli with PC diagnosis in a volunteer-sampled 235-person cohort from two institutional practices (UT San Antonio). We then used colibactin 742 and DNA/RNA sequencing to evaluate the effects of colibactin 742, dihydrotestosterone (DHT), and their combination in vitro.

KEY FINDINGS AND LIMITATIONS

Colibactin exposure was positively associated with PC diagnosis (p = 0.04) in our clinical cohort, and significantly increased replication fork stalling and fusions in vitro (p < 0.01). Combined in vitro exposure to colibactin 742 and DHT induced more somatic mutations of all types than exposure to either alone. The combination also elicited kataegis, with a higher density of somatic point mutations. Laboratory analyses were conducted using a single cell line, which limited our ability to fully recapitulate the complexity of PC etiology.

CONCLUSIONS AND CLINICAL IMPLICATIONS

Our findings are consistent with synergistic induction of genome instability and kataegis by colibactin 742 and DHT in cell culture. Colibactin-producing pks+ E. coli may plausibly contribute to PC etiology.

PATIENT SUMMARY

We investigated whether a bacterial toxin that is linked to colon cancer can also cause prostate cancer. Our results support this idea by showing a link between the toxin and prostate cancer diagnosis in a large patient population. We also found that this toxin causes genetic dysfunction in prostate cancer cells when combined with testosterone.

Machine learning based androgen receptor regulatory gene-related random forest survival model for precise treatment decision in prostate cancer

Background

It has been demonstrated that aberrant androgen receptor (AR) signaling contributes to the pathogenesis of prostate cancer (PCa). To date, the most efficacious strategy for the treatment of PCa remains to target the AR signaling axis. However, numerous PCa patients still face the issue of overtreatment or undertreatment. The establishment of a precise risk prediction model is urgently needed to distinguish patients with high-risk and select appropriate treatment modalities.

Methods

In this study, a consensus AR regulatory gene-related signature (ARS) was developed by integrating a total of 101 algorithm combinations of 10 machine learning algorithms. We evaluated the value of ARS in predicting patient prognosis and the therapeutic effects of the various treatments. Additionally, we conducted a screening of therapeutic targets and agents for high-risk patients, followed by the verification in vitro and in vivo.

Results

ARS was an independent risk factor for biochemical recurrence and distant metastasis in PCa patients. The enhanced and consistent prognostic predictive capability of ARS across various platforms was confirmed when compared with 44 previously published signatures. More importantly, PCa patients in the ARShigh group benefit more from PARP inhibitors and immunotherapy, while chemotherapy, radiotherapy, and AR-targeted therapy are more effective for ARSlow patients. The results of in silico screening suggest that AURKB could potentially serve as a promising therapeutic target for ARShigh patients.

Conclusions

Collectively, this prediction model based on AR regulatory genes holds great clinical translational potential to solve the dilemma of treatment choice and identify potential novel therapeutic targets in PCa.

Tumor evolution metrics predict recurrence beyond 10 years in locally advanced prostate cancer

Cancer evolution lays the groundwork for predictive oncology. Testing evolutionary metrics requires quantitative measurements in controlled clinical trials. We mapped genomic intratumor heterogeneity in locally advanced prostate cancer using 642 samples from 114 individuals enrolled in clinical trials with a 12-year median follow-up. We concomitantly assessed morphological heterogeneity using deep learning in 1,923 histological sections from 250 individuals. Genetic and morphological (Gleason) diversity were independent predictors of recurrence (hazard ratio (HR) = 3.12 and 95% confidence interval (95% CI) = 1.34-7.3; HR = 2.24 and 95% CI = 1.28-3.92). Combined, they identified a group with half the median time to recurrence. Spatial segregation of clones was also an independent marker of recurrence (HR = 2.3 and 95% CI = 1.11-4.8). We identified copy number changes associated with Gleason grade and found that chromosome 6p loss correlated with reduced immune infiltration. Matched profiling of relapse, decades after diagnosis, confirmed that genomic instability is a driving force in prostate cancer progression. This study shows that combining genomics with artificial intelligence-aided histopathology leads to the identification of clinical biomarkers of evolution.

Correlation of syndecan gene amplification with metastatic potential and clinical outcomes in carcinomas

Cell surface receptors play crucial roles in cellular responses to extracellular ligands, helping to modulate the functions of a cell based on information coming from outside the cell. Syndecan refers to a family of cell adhesion receptors that regulate both extracellular and cytosolic events. Alteration of syndecan expression disrupts regulatory mechanisms in a cell type-specific fashion, often leading to serious diseases, notably cancer. Given the multifaceted functions and distinct tissue distributions of syndecan, it will be important to unravel the gene-level intricacies of syndecan expression and thereby further understand its involvement in various carcinogenic processes. Although accumulating evidence indicates that the protein expression patterns of syndecan family members are significantly altered in cancer cells, the underlying gene-level mechanisms remain largely unknown. This review endeavors to explore syndecan gene expression levels across different cancer types by scrutinizing extensive cancer genome datasets using tools such as cBioPortal. Our analysis unveils that somatic mutations in SDC genes are rare occurrences, whereas copy number alterations are frequently observed across diverse cancers, particularly in SDC2 and SDC4. Notably, amplifications of SDC2 and SDC4 correlate with heightened metastatic potential and dismal prognosis. This underscores the recurrent nature of SDC2 and SDC4 amplifications during carcinogenesis and sheds light on their role in promoting cancer activity through augmented protein expression. The identification of these amplifications not only enriches our understanding of carcinogenic mechanisms but also hints at the potential therapeutic avenue of targeting SDC2 and SDC4 to curb cancer cell proliferation and metastasis.

Copy number signatures and CCNE1 amplification reveal the involvement of replication stress in high-grade endometrial tumors oncogenesis

PURPOSE

Managing high-grade endometrial cancer in Martinique poses significant challenges. The diversity of copy number alterations in high-grade endometrial tumors, often associated with a TP53 mutation, is a key factor complicating treatment. Due to the high incidence of high-grade tumors with poor prognosis, our study aimed to characterize the molecular signature of these tumors within a cohort of 25 high-grade endometrial cases.

METHODS

We conducted a comprehensive pangenomic analysis to categorize the copy number alterations involved in these tumors. Whole-Exome Sequencing (WES) and Homologous Recombination (HR) analysis were performed. The alterations obtained from the WES were classified into various signatures using the Copy Number Signatures tool available in COSMIC.

RESULTS

We identified several signatures that correlated with tumor stage and disctinct prognoses. These signatures all seem to be linked to replication stress, with CCNE1 amplification identified as the primary driver of oncogenesis in over 70% of tumors analyzed.

CONCLUSION

The identification of CCNE1 amplification, which is currently being explored as a therapeutic target in clinical trials, suggests new treatment strategies for high-grade endometrial cancer. This finding holds particular significance for Martinique, where access to care is challenging.

Dual inhibition of ATR and DNA-PKcs radiosensitizes ATM-mutant prostate cancer

In advanced castration resistant prostate cancer (CRPC), mutations in the DNA damage response (DDR) gene ataxia telangiectasia mutated ( ATM ) are common. While poly(ADP-ribose) polymerase inhibitors are approved in this context, their clinical efficacy remains limited. Thus, there is a compelling need to identify alternative therapeutic avenues for ATM mutant prostate cancer patients. Here, we generated matched ATM-proficient and ATM-deficient CRPC lines to elucidate the impact of ATM loss on DDR in response to DNA damage via irradiation. Through unbiased phosphoproteomic screening, we unveiled that ATM-deficient CRPC lines maintain dependence on downstream ATM targets through activation of ATR and DNA-PKcs kinases. Dual inhibition of ATR and DNA-PKcs effectively inhibited downstream γH2AX foci formation in response to irradiation and radiosensitized ATM-deficient lines to a greater extent than either ATM-proficient controls or single drug treatment. Further, dual inhibition abrogated residual downstream ATM pathway signaling and impaired replication fork dynamics. To circumvent potential toxicity, we leveraged the RUVBL1/2 ATPase inhibitor Compound B, which leads to the degradation of both ATR and DNA-PKcs kinases. Compound B effectively radiosensitized ATM-deficient CRPC in vitro and in vivo , and impacted replication fork dynamics. Overall, dual targeting of both ATR and DNA-PKcs is necessary to block DDR in ATM-deficient CRPC, and Compound B could be utilized as a novel therapy in combination with irradiation in these patients.

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.

Optimal systemic therapy in men with low-volume prostate cancer

PURPOSE OF REVIEW

Low-volume prostate cancer is an established prognostic category of metastatic hormone-sensitive prostate cancer. However, the term is often loosely used to reflect the low burden of disease across different prostate cancer states. This review explores the definitions of low-volume prostate cancer, biology, and current evidence for treatment. We also explore future directions, including the impact of advanced imaging modalities, particularly prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans, on refining patient subgroups and treatment strategies for patients with low-volume prostate cancer.

RECENT FINDINGS

Recent investigations have attempted to redefine low-volume disease, incorporating factors beyond metastatic burden. Advanced imaging, especially PSMA PET, offers enhanced accuracy in detecting metastases, potentially challenging the conventional definition of low volume. The prognosis and treatment of low-volume prostate cancer may vary by the timing of metastatic presentation. Biomarker-directed consolidative therapy, metastases-directed therapy, and de-escalation of systemic therapies will be increasingly important, especially in patients with metachronous low-volume disease.

SUMMARY

In the absence of validated biomarkers, the management of low-volume prostate cancer as defined by CHAARTED criteria may be guided by the timing of metastatic presentation. For metachronous low-volume disease, we recommend novel hormonal therapy (NHT) doublets with or without consolidative metastasis-directed therapy (MDT), and for synchronous low-volume disease, NHT doublets with or without consolidative MDT and prostate-directed radiation. Docetaxel triplets may be a reasonable alternative in some patients with synchronous presentation. There is no clear role of docetaxel doublets in patients with low-volume disease. In the future, a small subset of low-volume diseases with oligometastases selected by genomics and advanced imaging like PSMA PET may achieve long-term remission with MDT with no systemic therapy.

ProstaMine: a bioinformatics tool for identifying subtype-specific co-alterations associated with aggressiveness in prostate cancer

Background

Prostate cancer is a leading cause of cancer-related deaths among men, marked by heterogeneous clinical and molecular characteristics. The complexity of the molecular landscape necessitates tools for identifying multi-gene co-alteration patterns that are associated with aggressive disease. The identification of such gene sets will allow for deeper characterization of the processes underlying prostate cancer progression and potentially lead to novel strategies for treatment.

Methods

We developed ProstaMine to systematically identify co-alterations associated with aggressiveness in prostate cancer molecular subtypes defined by high-fidelity alterations in primary prostate cancer. ProstaMine integrates genomic, transcriptomic, and clinical data from five primary and one metastatic prostate cancer cohorts to prioritize co-alterations enriched in metastatic disease and associated with disease progression.

Results

Integrated analysis of primary tumors defined a set of 17 prostate cancer alterations associated with aggressive characteristics. We applied ProstaMine to NKX3-1-loss and RB1-loss tumors and identified subtype-specific co-alterations associated with metastasis and biochemical relapse in these molecular subtypes. In NKX3-1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations known to regulate prostate cancer signaling pathways including MAPK, NF-kB, p53, PI3K, and Sonic hedgehog. In RB1-loss prostate cancer, ProstaMine identified novel subtype-specific co-alterations involved in p53, STAT6, and MHC class I antigen presentation. Co-alterations impacting autophagy were noted in both molecular subtypes.

Conclusion

ProstaMine is a method to systematically identify novel subtype-specific co-alterations associated with aggressive characteristics in prostate cancer. The results from ProstaMine provide insights into potential subtype-specific mechanisms of prostate cancer progression which can be formed into testable experimental hypotheses. ProstaMine is publicly available at: https://bioinformatics.cuanschutz.edu/prostamine.

Predicting prostate cancer recurrence: Introducing PCRPS, an advanced online web server

Background

Prostate cancer (PCa) is one of the leading causes of cancer death in men. About 30% of PCa will develop a biochemical recurrence (BCR) following initial treatment, which significantly contributes to prostate cancer-related deaths. In clinical practice, accurate prediction of PCa recurrence is crucial for making informed treatment decisions. However, the development of reliable models and biomarkers for predicting PCa recurrence remains a challenge. In this study, the aim is to establish an effective and reliable tool for predicting the recurrence of PCa.

Methods

We systematically screened and analyzed potential datasets to predict PCa recurrence. Through quality control analysis, low-quality datasets were removed. Using meta-analysis, differential expression analysis, and feature selection, we identified key genes associated with recurrence. We also evaluated 22 previously published signatures for PCa recurrence prediction. To assess prediction performance, we employed nine machine learning algorithms. We compared the predictive capabilities of models constructed using clinical variables, expression data, and their combinations. Subsequently, we implemented these machine learning models into a user-friendly web server freely accessible to all researchers.

Results

Based on transcriptomic data derived from eight multicenter studies consisting of 733 PCa patients, we screened 23 highly influential genes for predicting prostate cancer recurrence. These genes were used to construct the Prostate Cancer Recurrence Prediction Signature (PCRPS). By comparing with 22 published signatures and four important clinicopathological features, the PCRPS exhibited a robust and significantly improved predictive capability. Among the tested algorithms, Random Forest demonstrated the highest AUC value of 0.72 in predicting PCa recurrence in the testing dataset. To facilitate access and usage of these machine learning models by all researchers and clinicians, we also developed an online web server (https://urology1926.shinyapps.io/PCRPS/) where the PCRPS model can be freely utilized. The tool can also be used to (1) predict the PCa recurrence by clinical information or expression data with high accuracy. (2) provide the possibility of PCa recurrence by nine machine learning algorithms. Furthermore, using the PCRPS scores, we predicted the sensitivity of 22 drugs from GDSC2 and 95 drugs from CTRP2 to the samples. These predictions provide valuable insights into potential drug sensitivities related to the PCRPS score groups.

Conclusion

Overall, our study provides an attractive tool to further guide the clinical management and individualized treatment for PCa.

From complexity to clarity: unravelling tumor heterogeneity through the lens of tumor microenvironment for innovative cancer therapy

Despite the tremendous clinical successes recorded in the landscape of cancer therapy, tumor heterogeneity remains a formidable challenge to successful cancer treatment. In recent years, the emergence of high-throughput technologies has advanced our understanding of the variables influencing tumor heterogeneity beyond intrinsic tumor characteristics. Emerging knowledge shows that drivers of tumor heterogeneity are not only intrinsic to cancer cells but can also emanate from their microenvironment, which significantly favors tumor progression and impairs therapeutic response. Although much has been explored to understand the fundamentals of the influence of innate tumor factors on cancer diversity, the roles of the tumor microenvironment (TME) are often undervalued. It is therefore imperative that a clear understanding of the interactions between the TME and other tumor intrinsic factors underlying the plastic molecular behaviors of cancers be identified to develop patient-specific treatment strategies. This review highlights the roles of the TME as an emerging factor in tumor heterogeneity. More particularly, we discuss the role of the TME in the context of tumor heterogeneity and explore the cutting-edge diagnostic and therapeutic approaches that could be used to resolve this recurring clinical conundrum. We conclude by speculating on exciting research questions that can advance our understanding of tumor heterogeneity with the goal of developing customized therapeutic solutions.

GraphPath: a graph attention model for molecular stratification with interpretability based on the pathway-pathway interaction network

MOTIVATION

Studying the molecular heterogeneity of cancer is essential for achieving personalized therapy. At the same time, understanding the biological processes that drive cancer development can lead to the identification of valuable therapeutic targets. Therefore, achieving accurate and interpretable clinical predictions requires paramount attention to thoroughly characterizing patients at both the molecular and biological pathway levels.

RESULTS

Here, we present GraphPath, a biological knowledge-driven graph neural network with multi-head self-attention mechanism that implements the pathway-pathway interaction network. We train GraphPath to classify the cancer status of patients with prostate cancer based on their multi-omics profiling. Experiment results show that our method outperforms P-NET and other baseline methods. Besides, two external cohorts are used to validate that the model can be generalized to unseen samples with adequate predictive performance. We reduce the dimensionality of latent pathway embeddings and visualize corresponding classes to further demonstrate the optimal performance of the model. Additionally, since GraphPath's predictions are interpretable, we identify target cancer-associated pathways that significantly contribute to the model's predictions. Such a robust and interpretable model has the potential to greatly enhance our understanding of cancer's biological mechanisms and accelerate the development of targeted therapies.

AVAILABILITY AND IMPLEMENTATION

https://github.com/amazingma/GraphPath.

The genomic and evolutionary landscapes of anaplastic thyroid carcinoma

Anaplastic thyroid carcinoma is arguably the most lethal human malignancy. It often co-occurs with differentiated thyroid cancers, yet the molecular origins of its aggressivity are unknown. We sequenced tumor DNA from 329 regions of thyroid cancer, including 213 from patients with primary anaplastic thyroid carcinomas. We also whole genome sequenced 9 patients using multi-region sequencing of both differentiated and anaplastic thyroid cancer components. Using these data, we demonstrate thatanaplastic thyroid carcinomas have a higher burden of mutations than other thyroid cancers, with distinct mutational signatures and molecular subtypes. Further, different cancer driver genes are mutated in anaplastic and differentiated thyroid carcinomas, even those arising in a single patient. Finally, we unambiguously demonstrate that anaplastic thyroid carcinomas share a genomic origin with co-occurring differentiated carcinomas and emerge from a common malignant field through acquisition of characteristic clonal driver mutations.

Genomic evolution shapes prostate cancer disease type

The development of cancer is an evolutionary process involving the sequential acquisition of genetic alterations that disrupt normal biological processes, enabling tumor cells to rapidly proliferate and eventually invade and metastasize to other tissues. We investigated the genomic evolution of prostate cancer through the application of three separate classification methods, each designed to investigate a different aspect of tumor evolution. Integrating the results revealed the existence of two distinct types of prostate cancer that arise from divergent evolutionary trajectories, designated as the Canonical and Alternative evolutionary disease types. We therefore propose the evotype model for prostate cancer evolution wherein Alternative-evotype tumors diverge from those of the Canonical-evotype through the stochastic accumulation of genetic alterations associated with disruptions to androgen receptor DNA binding. Our model unifies many previous molecular observations, providing a powerful new framework to investigate prostate cancer disease progression.

Multi-omics approach for identifying CNV-associated lncRNA signatures with prognostic value in prostate cancer

BACKGROUND

Prostate cancer, the second most prevalent malignancy among men, poses a significant threat to affected patients' well-being due to its poor prognosis. Novel biomarkers are required to enhance clinical outcomes and tailor personalized treatments. Herein, we describe our research to explore the prognostic value of long non-coding RNAs (lncRNAs) deregulated by copy number variations (CNVs) in prostate cancer.

METHODS

The study employed an integrative multi-omics data analysis of the prostate cancer transcriptomic, CNV and methylation datasets to identify prognosis-related subtypes. Subtype-specific expression profiles of protein-coding genes (PCGs) and lncRNAs were determined. We analysed CNV patterns of lncRNAs across the genome to identify subtype-specific lncRNAs with CNV changes. LncRNAs exhibiting significant amplification or deletion and a positive correlation were designated CNV-deregulated lncRNAs. A prognostic risk score model was subsequently developed using these CNV-driven lncRNAs.

RESULTS

Six molecular subtypes of prostate cancer were identified, demonstrating significant differences in prognosis (P = 0.034). The CNV profiles of subtype-specific lncRNAs were examined, revealing their correlation with CNV amplification or deletion. Six lncRNAs (CCAT2, LINC01593, LINC00276, GACAT2, LINC00457, LINC01343) were selected based on significant CNV amplifications or deletions using a rigorous univariate Cox proportional risk regression model. A robust risk score model was developed, stratifying patients into high-risk and low-risk categories. Notably, our prognostic model based on these six lncRNAs exhibited exceptional predictive capabilities for recurrence-free survival (RFS) in prostate cancer patients (P = 0.024).

CONCLUSIONS

Our study successfully identified a prognostic risk score model comprising six CNV-driven lncRNAs that could potentially be prognostic biomarkers for prostate cancer. These lncRNA signatures are closely associated with RFS, providing promising prospects for improved patient prognostication and personalized therapeutic strategies for novel prostate cancer treatment.

Machine learning-based extrachromosomal DNA identification in large-scale cohorts reveals its clinical implications in cancer

The clinical implications of extrachromosomal DNA (ecDNA) in cancer therapy remain largely elusive. Here, we present a comprehensive analysis of ecDNA amplification spectra and their association with clinical and molecular features in multiple cohorts comprising over 13,000 pan-cancer patients. Using our developed computational framework, GCAP, and validating it with multifaceted approaches, we reveal a consistent pan-cancer pattern of mutual exclusivity between ecDNA amplification and microsatellite instability (MSI). In addition, we establish the role of ecDNA amplification as a risk factor and refine genomic subtypes in a cohort from 1015 colorectal cancer patients. Importantly, our investigation incorporates data from four clinical trials focused on anti-PD-1 immunotherapy, demonstrating the pivotal role of ecDNA amplification as a biomarker for guiding checkpoint blockade immunotherapy in gastrointestinal cancer. This finding represents clinical evidence linking ecDNA amplification to the effectiveness of immunotherapeutic interventions. Overall, our study provides a proof-of-concept of identifying ecDNA amplification from cancer whole-exome sequencing (WES) data, highlighting the potential of ecDNA amplification as a valuable biomarker for facilitating personalized cancer treatment.

Acquired copy number variation in prostate tumours: a review of common somatic copy number alterations, how they are formed and their clinical utility

Prostate cancer is one of the most commonly diagnosed cancers in men and unfortunately, disease will progress in up to a third of patients despite primary treatment. Currently, there is a significant lack of prognostic tests that accurately predict disease course; however, the acquisition of somatic chromosomal variation in the form of DNA copy number variants may help understand disease progression. Notably, studies have found that a higher burden of somatic copy number alterations (SCNA) correlates with more aggressive disease, recurrence after surgery and metastasis. Here we will review the literature surrounding SCNA formation, including the roles of key tumour suppressors and oncogenes (PTEN, BRCA2, NKX3.1, ERG and AR), and their potential to inform diagnostic and prognostic clinical testing to improve predictive value. Ultimately, SCNAs, or inherited germline alterations that predispose to SCNAs, could have significant clinical utility in diagnostic and prognostic tests, in addition to guiding therapeutic selection.

Association between copy number alterations estimated using low-pass whole genome sequencing of formalin-fixed paraffin-embedded prostate tumor tissue and cancer-specific clinical parameters

Copy number alterations (CNAs) are frequently observed in early-stage prostate cancer and are associated with disease recurrence and tumor aggressiveness. Cost-effective assessment of CNAs could enhance clinical utility of CNAs. Here, we combined the cost-effectiveness of low-pass (low coverage) whole genome sequencing (LPWGS) and the routine availability of formalin-fixed paraffin-embedded (FFPE) tumor tissue for assessing CNAs in a cohort of 187 men with early-stage localised prostate cancer. We detected well known CNAs in 8p, 8q, 13q and 16q and recurrent gains of the oncogene MYC and losses of the tumor suppressor genes NKX3-1, PTEN and RB1, indicating assay reliability. The estimated burden of CNAs was significantly associated with Gleason score, pathological T stage, surgical margin status and biochemical recurrence. Further, genomic losses or gains in specific chromosomal arms were significantly associated with worse BCR-free survival. Copy number signatures extracted from the LPWGS data showed potential for risk stratifying patients, where signatures S1 and S2 showed significant association to worse BCR-free survival compared to S3. Our study provides clinical validation of the associations between CNAs and tumor aggressiveness in an independent and representative RP cohort, while demonstrating the feasibility of performing LPWGS of FFPE tumor tissue for cost-effective assessment of CNAs.

Hyper-Dependence on NHEJ Enables Synergy between DNA-PK Inhibitors and Low-Dose Doxorubicin in Leiomyosarcoma

PURPOSE

Leiomyosarcoma (LMS) is an aggressive sarcoma for which standard chemotherapies achieve response rates under 30%. There are no effective targeted therapies against LMS. Most LMS are characterized by chromosomal instability (CIN), resulting in part from TP53 and RB1 co-inactivation and DNA damage repair defects. We sought to identify therapeutic targets that could exacerbate intrinsic CIN and DNA damage in LMS, inducing lethal genotoxicity.

EXPERIMENTAL DESIGN

We performed clinical targeted sequencing in 287 LMS and genome-wide loss-of-function screens in 3 patient-derived LMS cell lines, to identify LMS-specific dependencies. We validated candidate targets by biochemical and cell-response assays in vitro and in seven mouse models.

RESULTS

Clinical targeted sequencing revealed a high burden of somatic copy-number alterations (median fraction of the genome altered =0.62) and demonstrated homologous recombination deficiency signatures in 35% of LMS. Genome-wide short hairpin RNA screens demonstrated PRKDC (DNA-PKcs) and RPA2 essentiality, consistent with compensatory nonhomologous end joining (NHEJ) hyper-dependence. DNA-PK inhibitor combinations with unconventionally low-dose doxorubicin had synergistic activity in LMS in vitro models. Combination therapy with peposertib and low-dose doxorubicin (standard or liposomal formulations) inhibited growth of 5 of 7 LMS mouse models without toxicity.

CONCLUSIONS

Combinations of DNA-PK inhibitors with unconventionally low, sensitizing, doxorubicin dosing showed synergistic effects in LMS in vitro and in vivo models, without discernable toxicity. These findings underscore the relevance of DNA damage repair alterations in LMS pathogenesis and identify dependence on NHEJ as a clinically actionable vulnerability in LMS.

Fascin-1 expression is associated with neuroendocrine prostate cancer and directly suppressed by androgen receptor

BACKGROUND

Neuroendocrine prostate cancer (NEPC) is an aggressive form of prostate cancer, arising from resistance to androgen-deprivation therapies. However, the molecular mechanisms associated with NEPC development and invasiveness are still poorly understood. Here we investigated the expression and functional significance of Fascin-1 (FSCN1), a pro-metastasis actin-bundling protein associated with poor prognosis of several cancers, in neuroendocrine differentiation of prostate cancer.

METHODS

Differential expression analyses using Genome Expression Omnibus (GEO) database, clinical samples and cell lines were performed. Androgen or antagonist's cellular treatments and knockdown experiments were used to detect changes in cell morphology, molecular markers, migration properties and in vivo tumour growth. Chromatin immunoprecipitation-sequencing (ChIP-Seq) data and ChIP assays were analysed to decipher androgen receptor (AR) binding.

RESULTS

We demonstrated that FSCN1 is upregulated during neuroendocrine differentiation of prostate cancer in vitro, leading to phenotypic changes and NEPC marker expression. In human prostate cancer samples, FSCN1 expression is restricted to NEPC tumours. We showed that the androgen-activated AR downregulates FSCN1 expression and works as a transcriptional repressor to directly suppress FSCN1 expression. AR antagonists alleviate this repression. In addition, FSCN1 silencing further impairs in vivo tumour growth.

CONCLUSION

Collectively, our findings identify FSCN1 as an AR-repressed gene. Particularly, it is involved in NEPC aggressiveness. Our results provide the rationale for the future clinical development of FSCN1 inhibitors in NEPC patients.

Comparative and integrative analysis of transcriptomic and epigenomic-wide DNA methylation changes in African American prostate cancer

African American (AA) men have the highest incidence and mortality rate from Prostate cancer (PCa) than any other racial/ethnic group. To date, PCa genomic studies have largely under-represented tumour samples from AA men. We measured genome-wide DNA methylation in benign and tumor prostate tissues from AA men using the Illumina Infunium 850 K EPIC array. mRNA expression database from a subset of the AA biospecimen were used to assess correlation of transcriptome and methylation datasets. Genome-wide methylation analysis identified 11,460 probes that were significant (p < 0.01) and differentially methylated in AA PCa compared to normal prostate tissues and showed significant (p < 0.01) inverse-correlation with mRNA expression. Ingenuity pathway analysis and Gene Ontology analysis in our AA dataset compared with TCGA dataset showed similarities in methylation patterns: top candidate genes with significant hypermethylation and corresponding down-regulated gene expression were associated with biological pathways in hemidesmosome assembly, mammary gland development, epidermis development, hormone biosynthesis, and cell communication. In addition, top candidate genes with significant hypomethylation and corresponding up-regulated gene expression were associated with biological pathways in macrophage differentiation, cAMP-dependent protein kinase activity, protein destabilization, transcription co-repression, and fatty acid biosynthesis. In contrast, differences in genome-wide methylation in our AA dataset compared with TCGA dataset were enriched for genes in steroid signalling, immune signalling, chromatin structure remodelling and RNA processing. Overall, differential methylation of AMIGO3, IER3, UPB1, GRM7, TFAP2C, TOX2, PLSCR2, ZNF292, ESR2, MIXL1, BOLL, and FGF6 were significant and uniquely associated with PCa progression in our AA cohort.

Regulation of EZH2 Expression by INPP4B in Normal Prostate and Primary Prostate Cancer

The phosphatases INPP4B and PTEN are tumor suppressors that are lost in nearly half of advanced metastatic cancers. The loss of PTEN in prostate epithelium initially leads to an upregulation of several tumor suppressors that slow the progression of prostate cancer in mouse models. We tested whether the loss of INPP4B elicits a similar compensatory response in prostate tissue and whether this response is distinct from the one caused by the loss of PTEN. Knockdown of INPP4B but not PTEN in human prostate cancer cell lines caused a decrease in EZH2 expression. In Inpp4b-/- mouse prostate epithelium, EZH2 levels were decreased, as were methylation levels of histone H3. In contrast, Ezh2 levels were increased in the prostates of Pten-/- male mice. Contrary to PTEN, there was a positive correlation between INPP4B and EZH2 expression in normal human prostates and early-stage prostate tumors. Analysis of single-cell transcriptomic data demonstrated that a subset of EZH2-positive cells expresses INPP4B or PTEN, but rarely both, consistent with their opposing correlation with EZH2 expression. Unlike PTEN, INPP4B did not affect the levels of SMAD4 protein expression or Pml mRNA expression. Like PTEN, p53 protein expression and phosphorylation of Akt in Inpp4b-/- murine prostates were elevated. Taken together, the loss of INPP4B in the prostate leads to overlapping and distinct changes in tumor suppressor and oncogenic downstream signaling.

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.

Cancer origin tracing and timing in two high-risk prostate cancers using multisample whole genome analysis: prospects for personalized medicine

BACKGROUND

Prostate cancer (PrCa) genomic heterogeneity causes resistance to therapies such as androgen deprivation. Such heterogeneity can be deciphered in the context of evolutionary principles, but current clinical trials do not include evolution as an essential feature. Whether or not analysis of genomic data in an evolutionary context in primary prostate cancer can provide unique added value in the research and clinical domains remains an open question.

METHODS

We used novel processing techniques to obtain whole genome data together with 3D anatomic and histomorphologic analysis in two men (GP5 and GP12) with high-risk PrCa undergoing radical prostatectomy. A total of 22 whole genome-sequenced sites (16 primary cancer foci and 6 lymph node metastatic) were analyzed using evolutionary reconstruction tools and spatio-evolutionary models. Probability models were used to trace spatial and chronological origins of the primary tumor and metastases, chart their genetic drivers, and distinguish metastatic and non-metastatic subclones.

RESULTS

In patient GP5, CDK12 inactivation was among the first mutations, leading to a PrCa tandem duplicator phenotype and initiating the cancer around age 50, followed by rapid cancer evolution after age 57, and metastasis around age 59, 5 years prior to prostatectomy. In patient GP12, accelerated cancer progression was detected after age 54, and metastasis occurred around age 56, 3 years prior to prostatectomy. Multiple metastasis-originating events were identified in each patient and tracked anatomically. Metastasis from prostate to lymph nodes occurred strictly ipsilaterally in all 12 detected events. In this pilot, metastatic subclone content analysis appears to substantially enhance the identification of key drivers. Evolutionary analysis' potential impact on therapy selection appears positive in these pilot cases.

CONCLUSIONS

PrCa evolutionary analysis allows tracking of anatomic site of origin, timing of cancer origin and spread, and distinction of metastatic-capable from non-metastatic subclones. This enables better identification of actionable targets for therapy. If extended to larger cohorts, it appears likely that similar analyses could add substantial biological insight and clinically relevant value.

Prospective clinical sequencing of 1016 Chinese prostate cancer patients: uncovering genomic characterization and race disparity

Although there is a well-known disparity in prostate cancer (PC) incidence and mortality between Chinese and Western patients, the underlying genomic differences have been investigated only sparsely. This clinicogenomic study was conducted to reveal the genomic mutations contributing to the PC disparity across ethnicities and investigate the mutational profile of Chinese PC patients. A total of 1016 Chinese PC patients were prospectively enrolled and subjected to targeted sequencing, resulting in usable sequencing data for 41 genes from 859 patients. Genomic data retrieved from The Cancer Genome Atlas (TCGA; locoregional PC), Memorial Sloan Kettering Cancer Center [MSKCC; metastatic castration-sensitive PC (mCSPC)], and Stand Up To Cancer [SU2C; metastatic castration-resistant PC (mCRPC)] cohorts were used as comparators representing Western men. Genomic mutations were analyzed using an integrated bioinformatic strategy. A comparison of the disease stages revealed that mutations in tumor protein 53 (TP53), androgen receptor (AR), forkhead box A1 (FOXA1), and genes involved in the cell cycle pathway were enriched in mCRPC. Mutations in adenomatous polyposis coli (APC) gene were found to be more prevalent in patients with visceral metastasis. Genomic differences between Western and Chinese men were mainly observed in castration-sensitive PC, with tumors from Chinese men having more FOXA1 (11.4% vs. 4.2%) but fewer TP53 (4.8% vs. 13%) mutations in locoregional PC and harboring fewer TP53 (11% vs. 29.2%), phosphatase and tensin homolog (PTEN; 2.5% vs. 10.3%), and APC (1.7% vs. 7.4%) mutations in the mCSPC stage than those of Western men. Patients of both ethnicities with mCRPC had similar mutational spectra. Furthermore, FOXA1 class-2 was less common than FOXA1 class-1 and showed no enrichment in metastasis, contrary to the findings in the Western cohort. Our study provides a valuable resource for a better understanding of PC in China and reveals the genomic alterations associated with PC disparity across races.

Chromosomal Copy Number Variation Predicts EGFR-TKI Response and Prognosis for Patients with Non-Small Cell Lung Cancer

Purpose

Chromosomal abnormalities represent genomic signatures linked to cancer prognosis and responses to chemotherapy, immunotherapy, and drug resistance. This study aimed to investigate the impact of chromosome copy number variants (CNVs) on the efficacy of tyrosine kinase inhibitors (TKIs) in EGFR-mutated non-small cell lung cancer (NSCLC) patients, as well as its prognostic implications for progression-free survival (PFS) and overall survival (OS) in EGFR wild-type patients.

Methods

A total of 110 patients with advanced NSCLC were enrolled in this study and categorized into EGFR-mutated and wild-type groups. Utilizing next-generation sequencing (NGS) technology, we assessed 24 genes and chromosome CNVs associated with lung cancer pathways in patients' tissue samples.

Results

Within the EGFR-mutated group, patients with a gain in Chr 1p13.3-p13.1 exhibited poor TKI responses, a high relapse rate, and shortened PFS (P = 0.002). Conversely, EGFR-mutated patients with a gain in 14q31.1-q31.3 demonstrated favorable TKI responses and relatively extended PFS (P = 0.005). Among EGFR wild-type patients, the presence of 7q31.1-q31.31 CNV emerged as an independent factor influencing both PFS and OS (P = 0.013, P = 0.004). Notably, patients with a gain in 7q31.1-q31.31 exhibited prolonged PFS and OS. Additionally, independent prognostic significance for OS in EGFR wild-type patients was observed for CNVs in 9q21.31-q22.2 and 11p11.11-q12.1 regions (P = 0.001). Patients with gains in these regions experienced extended OS, while losses were predictive of poorer outcomes.

Conclusion

Our results suggested that chromosomal copy number variation is a practical indicator for predicting the response of EGFR-targeted therapy and prognosis for NSCLC patients.

Copy number architectures define treatment-mediated selection of lethal prostate cancer clones

Despite initial responses to hormone treatment, metastatic prostate cancer invariably evolves to a lethal state. To characterize the intra-patient evolutionary relationships of metastases that evade treatment, we perform genome-wide copy number profiling and bespoke approaches targeting the androgen receptor (AR) on 167 metastatic regions from 11 organs harvested post-mortem from 10 men who died from prostate cancer. We identify diverse and patient-unique alterations clustering around the AR in metastases from every patient with evidence of independent acquisition of related genomic changes within an individual and, in some patients, the co-existence of AR-neutral clones. Using the genomic boundaries of pan-autosome copy number changes, we confirm a common clone of origin across metastases and diagnostic biopsies, and identified in individual patients, clusters of metastases occupied by dominant clones with diverged autosomal copy number alterations. These autosome-defined clusters are characterized by cluster-specific AR gene architectures, and in two index cases are topologically more congruent than by chance (p-values 3.07 × 10-8 and 6.4 × 10-4). Integration with anatomical sites suggests patterns of spread and points of genomic divergence. Here, we show that copy number boundaries identify treatment-selected clones with putatively distinct lethal trajectories.

GATA2 co-opts TGFβ1/SMAD4 oncogenic signaling and inherited variants at 6q22 to modulate prostate cancer progression

BACKGROUND

Aberrant somatic genomic alteration including copy number amplification is a hallmark of cancer genomes. We previously profiled genomic landscapes of prostate cancer (PCa), yet the underlying causal genes with prognostic potential has not been defined. It remains unclear how a somatic genomic event cooperates with inherited germline variants contribute to cancer predisposition and progression.

METHODS

We applied integrated genomic and clinical data, experimental models and bioinformatic analysis to identify GATA2 as a highly prevalent metastasis-associated genomic amplification in PCa. Biological roles of GATA2 in PCa metastasis was determined in vitro and in vivo. Global chromatin co-occupancy and co-regulation of GATA2 and SMAD4 was investigated by coimmunoprecipitation, ChIP-seq and RNA-seq assays. Tumor cellular assays, qRT-PCR, western blot, ChIP, luciferase assays and CRISPR-Cas9 editing methods were performed to mechanistically understand the cooperation of GATA2 with SMAD4 in promoting TGFβ1 and AR signaling and mediating inherited PCa risk and progression.

RESULTS

In this study, by integrated genomics and experimental analysis, we identified GATA2 as a prevalent metastasis-associated genomic amplification to transcriptionally augment its own expression in PCa. Functional experiments demonstrated that GATA2 physically interacted and cooperated with SMAD4 for genome-wide chromatin co-occupancy and co-regulation of PCa genes and metastasis pathways like TGFβ signaling. Mechanistically, GATA2 was cooperative with SMAD4 to enhance TGFβ and AR signaling pathways, and activated the expression of TGFβ1 via directly binding to a distal enhancer of TGFβ1. Strinkingly, GATA2 and SMAD4 globally mediated inherited PCa risk and formed a transcriptional complex with HOXB13 at the PCa risk-associated rs339331/6q22 enhancer, leading to increased expression of the PCa susceptibility gene RFX6.

CONCLUSIONS

Our study prioritizes causal genomic amplification genes with prognostic values in PCa and reveals the pivotal roles of GATA2 in transcriptionally activating the expression of its own and TGFβ1, thereby co-opting to TGFβ1/SMAD4 signaling and RFX6 at 6q22 to modulate PCa predisposition and progression.

A harmonized resource of integrated prostate cancer clinical, -omic, and signature features

Genomic and transcriptomic data have been generated across a wide range of prostate cancer (PCa) study cohorts. These data can be used to better characterize the molecular features associated with clinical outcomes and to test hypotheses across multiple, independent patient cohorts. In addition, derived features, such as estimates of cell composition, risk scores, and androgen receptor (AR) scores, can be used to develop novel hypotheses leveraging existing multi-omic datasets. The full potential of such data is yet to be realized as independent datasets exist in different repositories, have been processed using different pipelines, and derived and clinical features are often not provided or  not standardized. Here, we present the curatedPCaData R package, a harmonized data resource representing >2900 primary tumor, >200 normal tissue, and >500 metastatic PCa samples across 19 datasets processed using standardized pipelines with updated gene annotations. We show that meta-analysis across harmonized studies has great potential for robust and clinically meaningful insights. curatedPCaData is an open and accessible community resource with code made available for reproducibility.

Whole-exome sequencing of Indian prostate cancer reveals a novel therapeutic target: POLQ

PURPOSE

Prostate cancer is the second most common cancer diagnosed worldwide and the third most common cancer among men in India. This study's objective was to characterise the mutational landscape of Indian prostate cancer using whole-exome sequencing to identify population-specific polymorphisms.

METHODS

Whole-exome sequencing was performed of 58 treatment-naive primary prostate tumors of Indian origin. Multiple computational and statistical analyses were used to profile the known common mutations, other deleterious mutations, driver genes, prognostic biomarkers, and gene signatures unique to each clinical parameter. Cox analysis was performed to validate survival-associated genes. McNemar test identified genes significant to recurrence and receiver-operating characteristic (ROC) analysis was conducted to determine its accuracy. OncodriveCLUSTL algorithm was used to deduce driver genes. The druggable target identified was modeled with its known inhibitor using Autodock.

RESULTS

TP53 was the most commonly mutated gene in our cohort. Three novel deleterious variants unique to the Indian prostate cancer subtype were identified: POLQ, FTHL17, and OR8G1. COX regression analysis identified ACSM5, a mitochondrial gene responsible for survival. CYLC1 gene, which encodes for sperm head cytoskeletal protein, was identified as an unfavorable prognostic biomarker indicative of recurrence. The novel POLQ mutant, also identified as a driver gene, was evaluated as the druggable target in this study. POLQ, a DNA repair enzyme implicated in various cancer types, is overexpressed and is associated with a poor prognosis. The mutant POLQ was subjected to structural analysis and modeled with its known inhibitor novobiocin resulting in decreased binding efficiency necessitating the development of a better drug.

CONCLUSION

In this pilot study, the molecular profiling using multiple computational and statistical analyses revealed distinct polymorphisms in the Indian prostate cancer cohort. The mutational signatures identified provide a valuable resource for prognostic stratification and targeted treatment strategies for Indian prostate cancer patients. The DNA repair enzyme, POLQ, was identified as the druggable target in this study.

A DNA copy number alteration classifier as a prognostic tool for prostate cancer patients

BACKGROUND

Distinguishing between true indolent and potentially life-threatening prostate cancer is challenging in tumours displaying clinicopathologic features associated with low or intermediate risk of relapse. Several somatic DNA copy number alterations (CNAs) have been identified as potential prognostic biomarkers, but the standard cytogenetic method to assess them has a limited multiplexing capability.

METHODS

Multiplex ligation-dependent probe amplification (MLPA) targeting 14 genes was optimised to survey 448 tumours of patients with low or intermediate risk (Grade Group 1-3, Gleason score ≤7) who underwent radical prostatectomy. A 6-gene CNA classifier was developed using random survival forest and Cox proportional hazard modelling to predict biochemical recurrence.

RESULTS

The classifier score was significantly associated with biochemical recurrence after adjusting for standard clinicopathologic variables and the known prognostic index CAPRA-S score with a hazard ratio of 2.17 and 1.80, respectively (n = 406, P < 0.01). The prognostic value of this classifier was externally validated in published CNA data from three radical prostatectomy cohorts and one radiation therapy pre-treatment biopsy cohort.

CONCLUSION

The 6-gene CNA classifier generated by a single MLPA assay compatible with the small quantities of DNA extracted from formalin-fixed paraffin-embedded (FFPE) tissue specimens has the potential to improve the clinical management of patients with low or intermediate risk disease.

The Role of Immunotherapy or Immuno-Chemotherapy in Non-Small Cell Lung Cancer: A Comprehensive Review

Many new treatment modalities for non-small-cell carcinoma (NSCLC) have been described in the last two decades. Surgical resections remain the gold standard for early stages and may be considered for locally advanced tumors. Medical treatment has changed drastically in recent years, especially for advanced stages, for which the development of immunotherapy and molecular targeted therapy significantly increased survival and quality of life. The addition of radical surgical resection following immunotherapy or immuno-chemotherapy is feasible and safe with low surgical-related mortality and morbidity in selected patients with initially unresectable NSCLC. However, data from multiple ongoing trials with overall survival as the primary endpoint should be awaited before this strategy is introduced into the standard of care.

Prognostic Values of Gene Copy Number Alterations in Prostate Cancer

Whilst risk prediction for individual prostate cancer (PCa) cases is of a high priority, the current risk stratification indices for PCa management have severe limitations. This study aimed to identify gene copy number alterations (CNAs) with prognostic values and to determine if any combination of gene CNAs could have risk stratification potentials. Clinical and genomic data of 500 PCa cases from the Cancer Genome Atlas stable were retrieved from the Genomic Data Commons and cBioPortal databases. The CNA statuses of a total of 52 genetic markers, including 21 novel markers and 31 previously identified potential prognostic markers, were tested for prognostic significance. The CNA statuses of a total of 51/52 genetic markers were significantly associated with advanced disease at an odds ratio threshold of ≥1.5 or ≤0.667. Moreover, a Kaplan-Meier test identified 27/52 marker CNAs which correlated with disease progression. A Cox Regression analysis showed that the amplification of MIR602 and deletions of MIR602, ZNF267, MROH1, PARP8, and HCN1 correlated with a progression-free survival independent of the disease stage and Gleason prognostic group grade. Furthermore, a binary logistic regression analysis identified twenty-two panels of markers with risk stratification potentials. The best model of 7/52 genetic CNAs, which included the SPOP alteration, SPP1 alteration, CCND1 amplification, PTEN deletion, CDKN1B deletion, PARP8 deletion, and NKX3.1 deletion, stratified the PCa cases into a localised and advanced disease with an accuracy of 70.0%, sensitivity of 85.4%, specificity of 44.9%, positive predictive value of 71.67%, and negative predictive value of 65.35%. This study validated prognostic gene level CNAs identified in previous studies, as well as identified new genetic markers with CNAs that could potentially impact risk stratification in PCa.

The repertoire of copy number alteration signatures in human cancer

Copy number alterations (CNAs) are a predominant source of genetic alterations in human cancer and play an important role in cancer progression. However comprehensive understanding of the mutational processes and signatures of CNA is still lacking. Here we developed a mechanism-agnostic method to categorize CNA based on various fragment properties, which reflect the consequences of mutagenic processes and can be extracted from different types of data, including whole genome sequencing (WGS) and single nucleotide polymorphism (SNP) array. The 14 signatures of CNA have been extracted from 2778 pan-cancer analysis of whole genomes WGS samples, and further validated with 10 851 the cancer genome atlas SNP array dataset. Novel patterns of CNA have been revealed through this study. The activities of some CNA signatures consistently predict cancer patients' prognosis. This study provides a repertoire for understanding the signatures of CNA in cancer, with potential implications for cancer prognosis, evolution and etiology.

Preclinical models of prostate cancer - modelling androgen dependency and castration resistance in vitro, ex vivo and in vivo

Prostate cancer is well known to be dependent on the androgen receptor (AR) for growth and survival. Thus, AR is the main pharmacological target to treat this disease. However, after an initially positive response to AR-targeting therapies, prostate cancer will eventually evolve to castration-resistant prostate cancer, which is often lethal. Tumour growth was initially thought to become androgen-independent following treatments; however, results from molecular studies have shown that most resistance mechanisms involve the reactivation of AR. Consequently, tumour cells become resistant to castration - the blockade of testicular androgens - and not independent of AR per se. However, confusion still remains on how to properly define preclinical models of prostate cancer, including cell lines. Most cell lines were isolated from patients for cell culture after evolution of the tumour to castration-resistant prostate cancer, but not all of these cell lines are described as castration resistant. Moreover, castration refers to the blockade of testosterone production by the testes; thus, even the concept of "castration" in vitro is questionable. To ensure maximal transfer of knowledge from scientific research to the clinic, understanding the limitations and advantages of preclinical models, as well as how these models recapitulate cancer cell androgen dependency and can be used to study castration resistance mechanisms, is essential.