Molecular Evolution of Early-Onset Prostate Cancer Identifies Molecular Risk Markers and Clinical Trajectories

Oncogenic composite mutations can be predicted by co-mutations and their chromosomal location

Genetic heterogeneity in tumors can show a remarkable selectivity when two or more independent genetic events occur in the same gene. This phenomenon, called composite mutation, points toward a selective pressure, which frequently causes therapy resistance to mutation-specific drugs. Since composite mutations have been described to occur in sub-clonal populations, they are not always captured through biopsy sampling. Here, we provide a proof of concept to predict composite mutations to anticipate which patients might be at risk for sub-clonally driven therapy resistance. We found that composite mutations occur in 5% of cancer patients, mostly affecting the PIK3CA, EGFR, BRAF, and KRAS genes, which are common precision medicine targets. Furthermore, we found a strong and significant relationship between the frequencies of composite mutations with commonly co-occurring mutations in a non-composite context. We also found that co-mutations are significantly enriched on the same chromosome. These observations were independently confirmed using cell line data. Finally, we show the feasibility of predicting compositive mutations based on their co-mutations (AUC 0.62, 0.81, 0.82, and 0.91 for EGFR, PIK3CA, KRAS, and BRAF, respectively). This prediction model could help to stratify patients who are at risk of developing therapy resistance-causing mutations.

Unmasking Neuroendocrine Prostate Cancer with a Machine Learning-Driven 7-Gene Stemness Signature that Predicts Progression

Prostate cancer (PCa) poses a significant global health challenge, particularly due to its progression into aggressive forms like neuroendocrine prostate cancer (NEPC). This study developed and validated a stemness-associated gene signature using advanced machine learning techniques, including Random Forest and Lasso regression, applied to large-scale transcriptomic datasets. The resulting 7-gene signature ( KMT5C, MEN1, TYMS, IRF5, DNMT3B, CDC25B and DPP4 ) was validated across independent cohorts and patient-derived xenograft (PDX) models. The signature demonstrated strong prognostic value for progression-free, disease-free, relapse-free, metastasis-free, and overall survival. Importantly, the signature not only identified specific NEPC subtypes, such as large-cell neuroendocrine carcinoma, which is associated with very poor outcomes, but also predicted a poor prognosis for PCa cases that exhibit this molecular signature, even when they were not histopathologically classified as NEPC. This dual prognostic and classifier capability makes the 7-gene signature a robust tool for personalized medicine, providing a valuable resource for predicting disease progression and guiding treatment strategies in PCa management.

Asparagine Dependency Is a Targetable Metabolic Vulnerability in TP53-Altered Castration-Resistant Prostate Cancer

TP53 tumor suppressor is frequently altered in lethal, castration-resistant prostate cancer (CRPC). However, to date there are no effective treatments that specifically target TP53 alterations. Using transcriptomic and metabolomic analyses, we have shown here that TP53-altered prostate cancer exhibits an increased dependency on asparagine (Asn) and overexpresses Asn synthetase (ASNS), the enzyme catalyzing the synthesis of Asn. Mechanistically, the loss or mutation of TP53 transcriptionally activated ASNS expression, directly and via mTORC1-mediated ATF4 induction, driving de novo Asn biosynthesis to support CRPC growth. TP53-altered CRPC cells were sensitive to Asn restriction by knockdown of ASNS or L-asparaginase treatment to deplete the intracellular and extracellular sources of Asn, respectively, and cell viability was rescued by Asn addition. Notably, pharmacological inhibition of intracellular Asn biosynthesis using a glutaminase inhibitor and depletion of extracellular Asn with L-asparaginase significantly reduced Asn production and effectively impaired CRPC growth. This study highlights the significance of ASNS-mediated metabolic adaptation as a synthetic vulnerability in CRPC with TP53 alterations, providing a rationale for targeting Asn production to treat these lethal prostate cancers. Significance: TP53-mutated castration-resistant prostate cancer is dependent on asparagine biosynthesis due to upregulation of ASNS and can be therapeutically targeted by approaches that deplete intracellular and extracellular asparagine.

An 18-gene signature of recurrence-associated endothelial cells predicts tumor progression and castration resistance in prostate cancer

BACKGROUND

The prognostic and therapeutic implications of endothelial cells (ECs) heterogeneity in prostate cancer (PCa) are poorly understood.

METHODS

We investigated associations of EC heterogeneity with PCa recurrence and castration resistance in 8 bulk transcriptomic and 4 single-cell RNA-seq cohorts. A recurrence-associated EC (RAEC) signature was constructed by comparing 11 machine learning algorithms through nested cross-validation. Functional relevances of RAEC-specific genes were also tested.

RESULTS

A subset of ECs was significantly associated with recurrence in primary PCa and named RAECs. RAECs were characteristic of tip and immature cells and were enriched in migration, angiogenesis, and collagen-related pathways. We then developed an 18-gene RAEC signature (RAECsig) representative of RAECs. Higher RAECsig scores independently predicted tumor recurrence and performed better or comparably compared to clinicopathological factors and commercial gene signatures in multiple PCa cohorts. Of the 18 RAECsig genes, FSCN1 was upregulated in ECs from PCa with higher Gleason scores; and the silencing of FSCN1, TMEME255B, or GABRD in ECs either attenuated tube formation or inhibited PCa cell proliferation. Finally, higher RAECsig scores predicted castration resistance in both primary and castration-resistant PCa.

CONCLUSION

This study establishes an endothelial signature that links a subset of ECs to prostate cancer recurrence and castration resistance.

L1CAM mediates neuroendocrine phenotype acquisition in prostate cancer cells

BACKGROUND

A specific type of prostate cancer (PC) that exhibits neuroendocrine (NE) differentiation is known as NEPC. NEPC has little to no response to androgen deprivation therapy and is associated with the development of metastatic castration-resistant PC (CRPC), which has an extremely poor prognosis. Our understanding of genetic drivers and activated pathways in NEPC is limited, which hinders precision medicine approaches. L1 cell adhesion molecule (L1CAM) is known to play an oncogenic role in metastatic cancers, including CRPC. However, the impact of L1CAM on NEPC progression remains elusive.

METHODS

L1CAM expression level was investigated using public gene expression databases of PC cohorts and patient-derived xenograft models. L1CAM knockdown was performed in different PC cells to study in vitro cell functions. A subline of CRPC cell line CWR22Rv1 was established after long-term exposure to abiraterone to induce NE differentiation. The androgen receptor-negative cell line PC3 was cultured under the tumor sphere-forming condition to enrich cancer stemness features. Several oxidative stress inducers were tested on PC cells to observe L1CAM-mediated gene expression and cell death.

RESULTS

L1CAM expression was remarkably high in NEPC compared to CRPC or adenocarcinoma tumors. L1CAM was also correlated with NE marker expressions and associated with the adenocarcinoma-to-NEPC progression in gene expression databases and CRPC cells with NE differentiation. L1CAM also promoted cancer stemness and NE phenotypes in PC3 cells under cancer stemness enrichment. L1CAM was also identified as a reactive oxygen species-induced gene, by which L1CAM counteracted CRPC cell death triggered by ionizing radiation.

CONCLUSIONS

Our results unveiled a new role of L1CAM in the acquisition of the NE phenotype in PC, contributing to the NE differentiation-related therapeutic resistance of CRPC.

PRMT5-mediated FUBP1 methylation accelerates prostate cancer progression

Strategies beyond hormone-related therapy need to be developed to improve prostate cancer mortality. Here, we show that FUBP1 and its methylation were essential for prostate cancer progression, and a competitive peptide interfering with FUBP1 methylation suppressed the development of prostate cancer. FUBP1 accelerated prostate cancer development in various preclinical models. PRMT5-mediated FUBP1 methylation, regulated by BRD4, was crucial for its oncogenic effect and correlated with earlier biochemical recurrence in our patient cohort. Suppressed prostate cancer progression was observed in various genetic mouse models expressing the FUBP1 mutant deficient in PRMT5-mediated methylation. A competitive peptide, which was delivered through nanocomplexes, disrupted the interaction of FUBP1 with PRMT5, blocked FUBP1 methylation, and inhibited prostate cancer development in various preclinical models. Overall, our findings suggest that targeting FUBP1 methylation provides a potential therapeutic strategy for prostate cancer management.

Targeted gene sequencing reveals disparate genomic mutations between young and older adults in renal cell carcinoma

BACKGROUND

Renal cell carcinoma (RCC) is a type of cancer that can develop at any point in adulthood, spanning the range of age-related changes that occur in the body. However, the specific molecular mechanisms underlying the connections between age and genetic mutations in RCC have not been extensively investigated.

METHODS

Clinical and genetic data from patients diagnosed with RCC were collected from two prominent medical centers in China as well as the TCGA dataset. The patients were categorized into two groups based on their prognosticated age: young adults (YAs) and older adults (OAs). Univariate and multivariate analysis were employed to evaluate the relationships between age and genetic mutations. Furthermore, a mediation analysis was conducted to assess the association between age and overall survival, with genetic disparities serving as a mediator.

RESULTS

Our analysis revealed significant differences in clinical presentation between YAs and OAs with RCC, including histopathological types, histopathological tumor stage, and sarcomatoid differentiation. YAs were found to have lower mutation burden and significantly mutated genes (SMGs) of RCC. However, we did not observe any significant differences between the two groups in terms of 10 canonical oncogenic signaling pathways-related genes mutation, telomerase-related genes (TRGs) mutation, copy number changes, and genetic mutations associated with clinically actionable targeted drugs. Importantly, we demonstrate superior survival outcomes in YAs, and we confirmed the mediating effect of genetic disparities on these survival outcome differences between YAs and OAs.

CONCLUSION

Our findings reveal previously unrecognized associations between age and the molecular underpinnings of RCC. These associations may serve as valuable insights to guide precision diagnostics and treatments for RCC.

An Inherited Allele Confers Prostate Cancer Progression and Drug Resistance via RFX6/HOXA10-Orchestrated TGFβ Signaling

Genetic and epigenetic alterations are cancer hallmark characteristics. However, the role of inherited cancer predisposition alleles in co-opting lineage factor epigenetic reprogramming and tumor progression remains elusive. Here the FinnGen cohort phenome-wide analysis, along with multiple genome-wide association studies, has consistently identified the rs339331-RFX6/6q22 locus associated with prostate cancer (PCa) risk across diverse populations. It is uncovered that rs339331 resides in a reprogrammed androgen receptor (AR) binding site in PCa tumors, with the T risk allele enhancing AR chromatin occupancy. RFX6, an AR-regulated gene linked to rs339331, exhibits synergistic prognostic value for PCa recurrence and metastasis. This comprehensive in vitro and in vivo studies demonstrate the oncogenic functions of RFX6 in promoting PCa cell proliferation and metastasis. Mechanistically, RFX6 upregulates HOXA10 that profoundly correlates with adverse PCa outcomes and is pivotal in RFX6-mediated PCa progression, facilitating the epithelial-mesenchymal transition (EMT) and modulating the TGFβ/SMAD signaling axis. Clinically, HOXA10 elevation is associated with increased EMT scores, tumor advancement and PCa recurrence. Remarkably, reducing RFX6 expression restores enzalutamide sensitivity in resistant PCa cells and tumors. This findings reveal a complex interplay of genetic and epigenetic mechanisms in PCa pathogenesis and drug resistance, centered around disrupted prostate lineage AR signaling and abnormal RFX6 expression.

Characteristics of the immune environment in prostate cancer as an adjunct to immunotherapy

Background and Aims

The tumor microenvironment (TME) exerts an important role in carcinogenesis and progression. Several investigations have suggested that immune cell infiltration (ICI) is of high prognostic importance for tumor progression and patient survival in many tumors, particularly prostate cancer. The pattern of immune infiltration of PCa, on the other hand, has not been thoroughly understood.

Methods

The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets on PCa were obtained, and several datasets were merged into one data set using the "ComBat" algorithm. The ICI profiles of PCa patients were then to be uncovered by two computer techniques. The unsupervised clustering method was utilized to identify three ICI patterns in tumor samples, and Principal Component Analysis (PCA) was conducted to estimate the ICI score.

Results

Three different clusters of three ICIs were identified in 1341 PCa samples, which also correlated with different clinical features/characteristics and biological pathways. Patients with PCa are classified into high and low subtypes based on the ICI scores extracted from immune-associated signature genes. High ICI score subtypes are associated with a worse prognosis, which may intrigue the activation of cancer-related and immune-related pathways such as pathways involving Toll-like receptors, T-cell receptors, JAK-STAT, and natural killer cells. The ICI score was linked to tumor mutation load and immune/cancer-relevant signaling pathways, which explain prostate cancer's poor prognosis.

Conclusion

The findings of this study not only advanced our knowledge of the mechanism of immune response in the prostate tumor microenvironment but also provided a novel biomarker, that is, the ICI score, for disease prognosis and guiding precision immunotherapy.

Evolutionary screening of precision oncology biomarkers and its applications in prognostic model construction

Biomarker screening is critical for precision oncology. However, one of the main challenges in precision oncology is that the screened biomarkers often fail to achieve the expected clinical effects and are rarely approved by regulatory authorities. Considering the close association between cancer pathogenesis and the evolutionary events of organisms, we first explored the evolutionary feature underlying clinically approved biomarkers, and two evolutionary features of approved biomarkers (Ohnologs and specific evolutionary stages of genes) were identified. Subsequently, we utilized evolutionary features for screening potential prognostic biomarkers in four common cancers: head and neck squamous cell carcinoma, liver hepatocellular carcinoma, lung adenocarcinoma, and lung squamous cell carcinoma. Finally, we constructed an evolution-strengthened prognostic model (ESPM) for cancers. These models can predict cancer patients' survival time across different cancer cohorts effectively and perform better than conventional models. In summary, our study highlights the application potentials of evolutionary information in precision oncology biomarker screening.

A systematic analysis of the effects of splicing on the diversity of post-translational modifications in protein isoforms

Post-translational modifications (PTMs) and splicing are known to be important regulatory processes for controlling protein function and activity. However, there have been limitations in analyzing the interplay of alternative splicing and PTMs, which stems from the deep differences in genomic and proteomic databases. In this work, we bridged the protein- and genome-centric world views to map PTMs to genomic locations for subsequent projection of PTMs onto alternative isoforms. We then performed a systematic analysis of the diversification of PTMs by alternative splicing, including exploration of the modification-specific rates of inclusion across isoforms and how often the regulatory sequences directly flanking a PTM are impacted by splicing, which might indicate altered regulatory or binding interactions in the alternatively spliced isoform. We found that 6-51% of PTMs are excluded from at least one isoform, depending on the modification type. Further, approximately 2% of prospective PTM sites exhibited altered regulatory sequences surrounding the modification site, suggesting that regulatory or binding interactions might be diversified in these proteoforms. Lastly, we applied this PTM-to-isoform mapping approach to explore the impacts of disease-related splicing in prostate cancer, identifying possible new hypotheses explaining the variable consequences of ESRP1 expression in different cancers. As a part of this work, we have provided an easily implementable tool for annotating splice events identified from RNA-sequencing with PTMs and their functional consequences, called PTM-POSE.

[Prostate cancer screening-current overview]

BACKGROUND

The harm-to-benefit ratio of prostate cancer (PCa) screening remains controversial mainly due to the unfavorable test characteristics of prostate-specific antigen (PSA) as a screening test.

METHODS

In this nonsystematic review, we present a current overview of the body of evidence on prostate cancer screening with a focus on the role of magnetic resonance imaging (MRI) of the prostate.

RESULTS

Evidence generated in large randomized controlled trials showed that PSA-based screening significantly decreases cancer-specific mortality. The main obstacle in developing and implementing PCa screening strategies is the resulting overdiagnosis and as a consequence overtreatment of indolent cancers. Opportunistic screening is characterized by an adverse benefit-to-harm ratio and should, therefore, not be recommended. The German Statutory Early Detection Program for prostate cancer, which consists of a digital rectal examination (DRE) as a stand-alone screening test, is not evidence-based, neither specific nor sensitive enough and results in unnecessary diagnostics. The European Commission recently urged member states to develop population-based and organized risk-adapted PSA-based screening programs, which are currently tested in the ongoing German PROBASE trial. Finetuning of the diagnostic pathway following PSA-testing seems key to improve its positive and negative predictive value and thereby making PCa screening more accurate. Incorporation of prostatic MRI into screening strategies leads to more accurate diagnosis of clinically significant prostate cancer, while diagnosis of indolent cancers is reduced. In the future, molecular liquid-based biomarkers have the potential to complement or even replace PSA in PCa screening and further personalize screening strategies. Active surveillance as an alternative to immediate radical therapy of demographically increasing PCa diagnoses can potentially further improve the benefit-to-harm ratio of organized screening.

CONCLUSION

Early detection of PCa should be organized on a population level into personalized and evidence-based screening strategies. Multiparametric MRI of the prostate may play a key role in this setting.

Identifying proteomic risk factors for cancer using prospective and exome analyses of 1463 circulating proteins and risk of 19 cancers in the UK Biobank

The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.

Alternative splicing in prostate cancer progression and therapeutic resistance

Prostate cancer (CaP) remains the second leading cause of cancer deaths in western men. CaP mortality results from diverse molecular mechanisms that mediate resistance to the standard of care treatments for metastatic disease. Recently, alternative splicing has been recognized as a hallmark of CaP aggressiveness. Alternative splicing events cause treatment resistance and aggressive CaP behavior and are determinants of the emergence of the two major types of late-stage treatment-resistant CaP, namely castration-resistant CaP (CRPC) and neuroendocrine CaP (NEPC). Here, we review recent multi-omics data that are uncovering the complicated landscape of alternative splicing events during CaP progression and the impact that different gene transcript isoforms can have on CaP cell biology and behavior. We discuss renewed insights in the molecular machinery by which alternative splicing occurs and contributes to the failure of systemic CaP therapies. The potential for alternative splicing events to serve as diagnostic markers and/or therapeutic targets is explored. We conclude by considering current challenges and promises associated with splicing-modulating therapies, and their potential for clinical translation into CaP patient care.

Deciphering age-specific molecular features in cervical cancer and constructing an angio-immune prognostic model

Cancer incidence is increasingly seen in younger individuals. Molecular distinctions between young and elderly patients at onset are understudied. This study used public databases to explore genomic, transcriptomic, and immune-related features across age groups in cervical cancer. Additionally, it aims to create a prognostic model applicable across diverse age cohorts, enabling precise patient stratification, and personalized therapies. Gene mutations, expression data, and clinicopathological information were obtained from 317 cervical cancer patients. These patients were divided into a young group and an old group based on the median age of onset. The characteristics of differential gene mutation, gene expression, and immune cells analysis were analyzed by R software. Finally, the prognostic model was constructed by univariate Cox, least absolute shrinkage and selection operator, and multivariate Cox regression analyses of angiogenic and immune gene sets. Its validity was further confirmed using an additional 300 cervical squamous cell carcinoma and endocervical adenocarcinoma tissues. Cervical cancer patients at elderly onset age exhibit a significantly higher frequency of NOTCH1 and TP53 driver mutations compared to young patients, along with a notably higher tumor mutational burden. However, there were no significant differences between the 2 groups in terms of genomic instability and age-related mutational signatures. Differential gene expression analysis revealed that the young group significantly upregulated interferon-alpha and gamma responses and exhibited significantly higher activity in multiple metabolic pathways. Immune microenvironment analysis indicated enrichment of dendritic cells and natural killer cells in the young group, while transforming growth factor-β signature was enriched in the elderly group, indicating a higher degree of immune exclusion. A multigene prognostic model based on angiogenesis and T cell immune gene sets showed excellent prognostic performance independent of clinical factors such as age. High-risk groups identified by the model exhibit significant activation of tumor-promoting processes, such as metastasis and angiogenesis. Our study reveals distinct patterns in cancer-driving mechanisms, biological processes, and immune system status between young and elderly patients at onset with cervical cancer. These findings shed light on the age-specific underlying mechanisms of carcinogenesis. Furthermore, an independent molecular prognostic model is constructed to provide valuable references for patient stratification and the development of potential drug targets.

Cellular senescence and metabolic reprogramming model based on bulk/single-cell RNA sequencing reveals PTGER4 as a therapeutic target for ccRCC

Clear cell renal cell carcinoma (ccRCC) is the prevailing histological subtype of renal cell carcinoma and has unique metabolic reprogramming during its occurrence and development. Cell senescence is one of the newly identified tumor characteristics. However, there is a dearth of methodical and all-encompassing investigations regarding the correlation between the broad-ranging alterations in metabolic processes associated with aging and ccRCC. We utilized a range of analytical methodologies, such as protein‒protein interaction network analysis and least absolute shrinkage and selection operator (LASSO) regression analysis, to form and validate a risk score model known as the senescence-metabolism-related risk model (SeMRM). Our study demonstrated that SeMRM could more precisely predict the OS of ccRCC patients than the clinical prognostic markers in use. By utilizing two distinct datasets of ccRCC, ICGC-KIRC (the International Cancer Genome Consortium) and GSE29609, as well as a single-cell dataset (GSE156632) and real patient clinical information, and further confirmed the relationship between the senescence-metabolism-related risk score (SeMRS) and ccRCC patient progression. It is worth noting that patients who were classified into different subgroups based on the SeMRS exhibited notable variations in metabolic activity, immune microenvironment, immune cell type transformation, mutant landscape, and drug responsiveness. We also demonstrated that PTGER4, a key gene in SeMRM, regulated ccRCC cell proliferation, lipid levels and the cell cycle in vivo and in vitro. Together, the utilization of SeMRM has the potential to function as a dependable clinical characteristic to increase the accuracy of prognostic assessment for patients diagnosed with ccRCC, thereby facilitating the selection of suitable treatment strategies.

ERG activates a stem-like proliferation-differentiation program in prostate epithelial cells with mixed basal-luminal identity

To gain insight into how ERG translocations cause prostate cancer, we performed single cell transcriptional profiling of an autochthonous mouse model at an early stage of disease initiation. Despite broad expression of ERG in all prostate epithelial cells, proliferation was enriched in a small, stem-like population with mixed-luminal basal identity (called intermediate cells). Through a series of lineage tracing and primary prostate tissue transplantation experiments, we find that tumor initiating activity resides in a subpopulation of basal cells that co-express the luminal genes Tmprss2 and Nkx3.1 (called BasalLum) but not in the larger population of classical Krt8+ luminal cells. Upon ERG activation, BasalLum cells give rise to the highly proliferative intermediate state, which subsequently transitions to the larger population of Krt8+ luminal cells characteristic of ERG-positive human cancers. Furthermore, this proliferative population is characterized by an ERG-specific chromatin state enriched for NFkB, AP-1, STAT and NFAT binding, with implications for TF cooperativity. The fact that the proliferative potential of ERG is enriched in a small stem-like population implicates the chromatin context of these cells as a critical variable for unmasking its oncogenic activity.

Combined SNPs sequencing and allele specific proteomics capture reveal functional causality underpinning the 2p25 prostate cancer susceptibility locus

Genome wide association studies (GWASs) have identified numerous risk loci associated with prostate cancer, yet unraveling their functional significance remains elusive. Leveraging our high-throughput SNPs-seq method, we pinpointed rs4519489 within the multi-ancestry GWAS-discovered 2p25 locus as a potential functional SNP due to its significant allelic differences in protein binding. Here, we conduct a comprehensive analysis of rs4519489 and its associated gene, NOL10, employing diverse cohort data and experimental models. Clinical findings reveal a synergistic effect between rs4519489 genotype and NOL10 expression on prostate cancer prognosis and severity. Through unbiased proteomics screening, we reveal that the risk allele A of rs4519489 exhibits enhanced binding to USF1, a novel oncogenic transcription factor (TF) implicated in prostate cancer progression and prognosis, resulting in elevated NOL10 expression. Furthermore, we elucidate that NOL10 regulates cell cycle pathways, fostering prostate cancer progression. The concurrent expression of NOL10 and USF1 correlates with aggressive prostate cancer characteristics and poorer prognosis. Collectively, our study offers a robust strategy for functional SNP screening and TF identification through high-throughput SNPs-seq and unbiased proteomics, highlighting the rs4519489-USF1-NOL10 regulatory axis as a promising biomarker or therapeutic target for clinical diagnosis and treatment of prostate cancer.

APOBEC shapes tumor evolution and age at onset of lung cancer in smokers

APOBEC enzymes are part of the innate immunity and are responsible for restricting viruses and retroelements by deaminating cytosine residues1,2. Most solid tumors harbor different levels of somatic mutations attributed to the off-target activities of APOBEC3A (A3A) and/or APOBEC3B (A3B)3-6. However, how APOBEC3A/B enzymes shape the tumor evolution in the presence of exogenous mutagenic processes is largely unknown. Here, by combining deep whole-genome sequencing with multi-omics profiling of 309 lung cancers from smokers with detailed tobacco smoking information, we identify two subtypes defined by low (LAS) and high (HAS) APOBEC mutagenesis. LAS are enriched for A3B-like mutagenesis and KRAS mutations, whereas HAS for A3A-like mutagenesis and TP53 mutations. Unlike APOBEC3A, APOBEC3B expression is strongly associated with an upregulation of the base excision repair pathway. Hypermutation by unrepaired A3A and tobacco smoking mutagenesis combined with TP53-induced genomic instability can trigger senescence7, apoptosis8, and cell regeneration9, as indicated by high expression of pulmonary healing signaling pathway, stemness markers and distal cell-of-origin in HAS. The expected association of tobacco smoking variables (e.g., time to first cigarette) with genomic/epigenomic changes are not observed in HAS, a plausible consequence of frequent cell senescence or apoptosis. HAS have more neoantigens, slower clonal expansion, and older age at onset compared to LAS, particularly in heavy smokers, consistent with high proportions of newly generated, unmutated cells and frequent immuno-editing. These findings show how heterogeneity in mutational burden across co-occurring mutational processes and cell types contributes to tumor development, with important clinical implications.

Race-specific coregulatory and transcriptomic profiles associated with DNA methylation and androgen receptor in prostate cancer

BACKGROUND

Prostate cancer is a significant health concern, particularly among African American (AA) men who exhibit higher incidence and mortality compared to European American (EA) men. Understanding the molecular mechanisms underlying these disparities is imperative for enhancing clinical management and achieving better outcomes.

METHODS

Employing a multi-omics approach, we analyzed prostate cancer in both AA and EA men. Using Illumina methylation arrays and RNA sequencing, we investigated DNA methylation and gene expression in tumor and non-tumor prostate tissues. Additionally, Boolean analysis was utilized to unravel complex networks contributing to racial disparities in prostate cancer.

RESULTS

When comparing tumor and adjacent non-tumor prostate tissues, we found that DNA hypermethylated regions are enriched for PRC2/H3K27me3 pathways and EZH2/SUZ12 cofactors. Olfactory/ribosomal pathways and distinct cofactors, including CTCF and KMT2A, were enriched in DNA hypomethylated regions in prostate tumors from AA men. We identified race-specific inverse associations of DNA methylation with expression of several androgen receptor (AR) associated genes, including the GATA family of transcription factors and TRIM63. This suggests that race-specific dysregulation of the AR signaling pathway exists in prostate cancer. To investigate the effect of AR inhibition on race-specific gene expression changes, we generated in-silico patient-specific prostate cancer Boolean networks. Our simulations revealed prolonged AR inhibition causes significant dysregulation of TGF-β, IDH1, and cell cycle pathways specifically in AA prostate cancer. We further quantified global gene expression changes, which revealed differential expression of genes related to microtubules, immune function, and TMPRSS2-fusion pathways, specifically in prostate tumors of AA men. Enrichment of these pathways significantly correlated with an altered risk of disease progression in a race-specific manner.

CONCLUSIONS

Our study reveals unique signaling networks underlying prostate cancer biology in AA and EA men, offering potential insights for clinical management strategies tailored to specific racial groups. Targeting AR and associated pathways could be particularly beneficial in addressing the disparities observed in prostate cancer outcomes in the context of AA and EA men. Further investigation into these identified pathways may lead to the development of personalized therapeutic approaches to improve outcomes for prostate cancer patients across different racial backgrounds.

Proteogenomic insights into early-onset endometrioid endometrial carcinoma: predictors for fertility-sparing therapy response

Endometrial carcinoma remains a public health concern with a growing incidence, particularly in younger women. Preserving fertility is a crucial consideration in the management of early-onset endometrioid endometrial carcinoma (EEEC), particularly in patients under 40 who maintain both reproductive desire and capacity. To illuminate the molecular characteristics of EEEC, we undertook a large-scale multi-omics study of 215 patients with endometrial carcinoma, including 81 with EEEC. We reveal an unexpected association between exposome-related mutational signature and EEEC, characterized by specific CTNNB1 and SIGLEC10 hotspot mutations and disruption of downstream pathways. Interestingly, SIGLEC10Q144K mutation in EEECs resulted in aberrant SIGLEC-10 protein expression and promoted progestin resistance by interacting with estrogen receptor alpha. We also identified potential protein biomarkers for progestin response in fertility-sparing treatment for EEEC. Collectively, our study establishes a proteogenomic resource of EEECs, uncovering the interactions between exposome and genomic susceptibilities that contribute to the development of primary prevention and early detection strategies for EEECs.

In vivo genome-wide CRISPR screening identifies CITED2 as a driver of prostate cancer bone metastasis

Most cancer deaths are due to metastatic dissemination to distant organs. Bone is the most frequently affected organ in metastatic prostate cancer and a major cause of prostate cancer deaths. Yet, our partial understanding of the molecular factors that drive bone metastasis has been a limiting factor for developing preventative and therapeutic strategies to improve patient survival and well-being. Although recent studies have uncovered molecular alterations that occur in prostate cancer metastasis, their functional relevance for bone metastasis is not well understood. Using genome-wide CRISPR activation and inhibition screens we have identified multiple drivers and suppressors of prostate cancer metastasis. Through functional validation, including an innovative organ-on-a-chip invasion platform for studying bone tropism, our study identifies the transcriptional modulator CITED2 as a novel driver of prostate cancer bone metastasis and uncovers multiple new potential molecular targets for bone metastatic disease.

Aging-related biomarker discovery in the era of immune checkpoint inhibitors for cancer patients

Older patients with cancer, particularly those over 75 years of age, often experience poorer clinical outcomes compared to younger patients. This can be attributed to age-related comorbidities, weakened immune function, and reduced tolerance to treatment-related adverse effects. In the immune checkpoint inhibitors (ICI) era, age has emerged as an influential factor impacting the discovery of predictive biomarkers for ICI treatment. These age-linked changes in the immune system can influence the composition and functionality of tumor-infiltrating immune cells (TIICs) that play a crucial role in the cancer response. Older patients may have lower levels of TIICs infiltration due to age-related immune senescence particularly T cell function, which can limit the effectivity of cancer immunotherapies. Furthermore, age-related immune dysregulation increases the exhaustion of immune cells, characterized by the dysregulation of ICI-related biomarkers and a dampened response to ICI. Our review aims to provide a comprehensive understanding of the mechanisms that contribute to the impact of age on ICI-related biomarkers and ICI response. Understanding these mechanisms will facilitate the development of treatment approaches tailored to elderly individuals with cancer.

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.

A platform-independent AI tumor lineage and site (ATLAS) classifier

Histopathologic diagnosis and classification of cancer plays a critical role in guiding treatment. Advances in next-generation sequencing have ushered in new complementary molecular frameworks. However, existing approaches do not independently assess both site-of-origin (e.g. prostate) and lineage (e.g. adenocarcinoma) and have minimal validation in metastatic disease, where classification is more difficult. Utilizing gradient-boosted machine learning, we developed ATLAS, a pair of separate AI Tumor Lineage and Site-of-origin models from RNA expression data on 8249 tumor samples. We assessed performance independently in 10,376 total tumor samples, including 1490 metastatic samples, achieving an accuracy of 91.4% for cancer site-of-origin and 97.1% for cancer lineage. High confidence predictions (encompassing the majority of cases) were accurate 98-99% of the time in both localized and remarkably even in metastatic samples. We also identified emergent properties of our lineage scores for tumor types on which the model was never trained (zero-shot learning). Adenocarcinoma/sarcoma lineage scores differentiated epithelioid from biphasic/sarcomatoid mesothelioma. Also, predicted lineage de-differentiation identified neuroendocrine/small cell tumors and was associated with poor outcomes across tumor types. Our platform-independent single-sample approach can be easily translated to existing RNA-seq platforms. ATLAS can complement and guide traditional histopathologic assessment in challenging situations and tumors of unknown primary.

A reliable transcriptomic risk-score applicable to formalin-fixed paraffin-embedded biopsies improves outcome prediction in localized prostate cancer

BACKGROUND

Clinical manifestation of prostate cancer (PCa) is highly variable. Aggressive tumors require radical treatment while clinically non-significant ones may be suitable for active surveillance. We previously developed the prognostic ProstaTrend RNA signature based on transcriptome-wide microarray and RNA-sequencing (RNA-Seq) analyses, primarily of prostatectomy specimens. An RNA-Seq study of formalin-fixed paraffin-embedded (FFPE) tumor biopsies has now allowed us to use this test as a basis for the development of a novel test that is applicable to FFPE biopsies as a tool for early routine PCa diagnostics.

METHODS

All patients of the FFPE biopsy cohort were treated by radical prostatectomy and median follow-up for biochemical recurrence (BCR) was 9 years. Based on the transcriptome data of 176 FFPE biopsies, we filtered ProstaTrend for genes susceptible to FFPE-associated degradation via regression analysis. ProstaTrend was additionally restricted to genes with concordant prognostic effects in the RNA-Seq TCGA prostate adenocarcinoma (PRAD) cohort to ensure robust and broad applicability. The prognostic relevance of the refined Transcriptomic Risk Score (TRS) was analyzed by Kaplan-Meier curves and Cox-regression models in our FFPE-biopsy cohort and 9 other public datasets from PCa patients with BCR as primary endpoint. In addition, we developed a prostate single-cell atlas of 41 PCa patients from 5 publicly available studies to analyze gene expression of ProstaTrend genes in different cell compartments.

RESULTS

Validation of the TRS using the original ProstaTrend signature in the cohort of FFPE biopsies revealed a relevant impact of FFPE-associated degradation on gene expression and consequently no significant association with prognosis (Cox-regression, p-value > 0.05) in FFPE tissue. However, the TRS based on the new version of the ProstaTrend-ffpe signature, which included 204 genes (of originally 1396 genes), was significantly associated with BCR in the FFPE biopsy cohort (Cox-regression p-value < 0.001) and retained prognostic relevance when adjusted for Gleason Grade Groups. We confirmed a significant association with BCR in 9 independent cohorts including 1109 patients. Comparison of the prognostic performance of the TRS with 17 other prognostically relevant PCa panels revealed that ProstaTrend-ffpe was among the best-ranked panels. We generated a PCa cell atlas to associate ProstaTrend genes with cell lineages or cell types. Tumor-specific luminal cells have a significantly higher TRS than normal luminal cells in all analyzed datasets. In addition, TRS of epithelial and luminal cells was correlated with increased Gleason score in 3 studies.

CONCLUSIONS

We developed a prognostic gene-expression signature for PCa that can be applied to FFPE biopsies and may be suitable to support clinical decision-making.

Identification of Molecular Markers Associated with Prostate Cancer Subtypes: An Integrative Bioinformatics Approach

Prostate cancer (PCa) is characterised by androgen dependency. Unfortunately, under anti-androgen treatment pressure, castration-resistant prostate cancer (CRPC) emerges, characterised by heterogeneous cell populations that, over time, lead to the development of different androgen-dependent or -independent phenotypes. Despite important advances in therapeutic strategies, CRPC remains incurable. Context-specific essential genes represent valuable candidates for targeted anti-cancer therapies. Through the investigation of gene and protein annotations and the integration of published transcriptomic data, we identified two consensus lists to stratify PCa patients' risk and discriminate CRPC phenotypes based on androgen receptor activity. ROC and Kaplan-Meier survival analyses were used for gene set validation in independent datasets. We further evaluated these genes for their association with cancer dependency. The deregulated expression of the PCa-related genes was associated with overall and disease-specific survival, metastasis and/or high recurrence risk, while the CRPC-related genes clearly discriminated between adeno and neuroendocrine phenotypes. Some of the genes showed context-specific essentiality. We further identified candidate drugs through a computational repositioning approach for targeting these genes and treating lethal variants of PCa. This work provides a proof-of-concept for the use of an integrative approach to identify candidate biomarkers involved in PCa progression and CRPC pathogenesis within the goal of precision medicine.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Role of epithelial splicing regulatory protein 1 in cancer progression

As aberrant alternative splicing by either dysregulation or mutations of splicing factors contributes to cancer initiation and progression, splicing factors are emerging as potential therapeutic targets for cancer therapy. Therefore, pharmacological modulators targeting splicing factors have been under development. Epithelial splicing regulatory protein 1 (ESRP1) is an epithelial cell-specific splicing factor, whose downregulation is associated with epithelial-mesenchymal transition (EMT) by regulating alternative splicing of multiple genes, such as CD44, CTNND1, ENAH, and FGFR2. Consistent with the downregulation of ESRP1 during EMT, it has been initially revealed that high ESRP1 expression is associated with favorable prognosis and ESRP1 plays a tumor-suppressive role in cancer progression. However, ESRP1 has been found to promote cancer progression in some cancers, such as breast and ovarian cancers, indicating that it plays a dual role in cancer progression depending on the type of cancer. Furthermore, recent studies have reported that ESRP1 affects tumor growth by regulating the metabolism of tumor cells or immune cell infiltration in the tumor microenvironment, suggesting the novel roles of ESRP1 in addition to EMT. ESRP1 expression was also associated with response to anticancer drugs. This review describes current understanding of the roles and mechanisms of ESRP1 in cancer progression, and further discusses the emerging novel roles of ESRP1 in cancer and recent attempts to target splicing factors for cancer therapy.

Aberrant expression of multiple glycolytic enzyme genes is significantly associated with disease progression and survival outcomes in prostate cancers

Prostate cancer is the leading cause of cancer death after lung cancer in men. Recent studies showed that aberrant metabolic pathways are involved in prostate cancer development and progression. In this study, we performed a systemic analysis of glycolytic enzyme gene expression using the TCGA-PRAD RNAseq dataset. Our analysis revealed that among 25 genes, only four genes (HK2/GPI/PFKL/PGAM5) were significantly upregulated while nine genes (HK1/GCK/PFKM/PFKP/ALDOC/PGK1/PGAM1/ENO2/PKM) were downregulated in primary prostate cancer tissues compared to benign compartments. Among these 13 altered genes, four genes (ENO2/ALDOC/GPI/GCK) exhibited strong diagnostic potential in distinguishing malignant and benign tissues. Meanwhile, GPI expression exerted as a prognostic factor of progression-free and disease-specific survival. PFKL and PGAM5 gene expressions were associated with AR signaling scores in castration-resistant patients, and AR-targeted therapy suppressed their expression. In LuCap35 xenograft tumors, PFKL and PGAM5 expression was significantly reduced after animal castration, confirming the AR dependency. Conversely, GCK/PKLR genes were significantly associated with neuroendocrinal progression, representing two novel neuroendocrinal biomarkers for prostate cancer. In conclusion, our results suggest that GPI expression is a strong prognostic factor for prostate cancer progression and survival while GCK/PKLR are two novel biomarkers of prostate cancer progression to neuroendocrinal status.

Expressions of glucose transporter genes are diversely attenuated and significantly associated with prostate cancer progression

Prostate cancer is a health-threaten disease in men worldwide, however, lacking is the reliable biomarkers for patient management. Aberrant metabolic events including glucose metabolism are involved in prostate cancer progression. To examine the involvement of glucose metabolic pathways in prostate cancer, we analyzed the expression profiles of glucose transporter family genes using multiple RNA-seq datasets. Our results showed that three SLC2A family genes (SLC2A4/5/9) were significantly downregulated in primary prostate cancers compared to their benign compartments. These down-regulated expressions were inversely correlated with their gene promoter methylation and genome abnormalities. Among these three SLC2A genes, only SLC2A4 showed a significantly reverse correlation with all clinicopathological parameters, including TNM stage, disease relapse, Gleason score, disease-specific survival, and progression-free interval. In addition, the expression levels of these three genes were strongly correlated with anti-cancer immune cell filtration in primary prostate cancers. In a group of patients with early-onset prostate cancers, SLC2A4 also showed a strong negative correlation with multiple clinicopathological parameters, such as tumor mutation burden, biochemical relapse, pre-surgical PSA levels, and Gleason score but a positive correlation with progression-free interval after surgery. In metastatic castration-resistant prostate cancers (CRPC), SLC2A9 gene expression but not SLC2A4 or SLC2A5 genes showed a significant correlation with androgen receptor (AR) activity score and neuroendocrinal (NE) activity score. Meanwhile, SLC2A2/9/13 expression was significantly elevated in CRPC tumors with neuroendocrinal features compared to those without NE features. On the other hand, SLC2A10 and SlC2A12 gene expression were significantly reduced in NEPC tumors compared to CRPC tumors. Consistently, SLC2A10/12 expression levels were significantly reduced in castrated animals carrying the LuCaP35 xenograft models. Survival outcome analysis revealed that SLC2A4 expression in primary tumors is a favorable prognostic factor and SLC2A6 is a worse prognostic factor for disease-specific survival and progression-free survival in prostate cancer patients. In conclusion, our results suggest that SLC2A4/6 expressions are strong prognostic factors for prostate cancer progression and survival. The significance of SLC2A2/9/13 over-expression during NEPC progression needs more investigation.

Integrated Genomic Analysis of Primary Prostate Tumor Foci and Corresponding Lymph Node Metastases Identifies Mutations and Pathways Associated with Metastasis

Prostate cancer is a highly heterogeneous disease and mortality is mainly due to metastases but the initial steps of metastasis have not been well characterized. We have performed integrative whole exome sequencing and transcriptome analysis of primary prostate tumor foci and corresponding lymph node metastases (LNM) from 43 patients enrolled in clinical trial. We present evidence that, while there are some cases of clonally independent primary tumor foci, 87% of primary tumor foci and metastases are descended from a common ancestor. We demonstrate that genes related to oxidative phosphorylation are upregulated in LNM and in African-American patients relative to White patients. We further show that mutations in TP53, FLT4, EYA1, NCOR2, CSMD3, and PCDH15 are enriched in prostate cancer metastases. These findings were validated in a meta-analysis of 3929 primary tumors and 2721 metastases and reveal a pattern of molecular alterations underlying the pathology of metastatic prostate cancer. We show that LNM contain multiple subclones that are already present in primary tumor foci. We observed enrichment of mutations in several genes including understudied genes such as EYA1, CSMD3, FLT4, NCOR2, and PCDH15 and found that mutations in EYA1 and CSMD3 are associated with a poor outcome in prostate cancer.

Integrative multi-omics analysis unveils stemness-associated molecular subtypes in prostate cancer and pan-cancer: prognostic and therapeutic significance

BACKGROUND

Prostate cancer (PCA) is the fifth leading cause of cancer-related deaths worldwide, with limited treatment options in the advanced stages. The immunosuppressive tumor microenvironment (TME) of PCA results in lower sensitivity to immunotherapy. Although molecular subtyping is expected to offer important clues for precision treatment of PCA, there is currently a shortage of dependable and effective molecular typing methods available for clinical practice. Therefore, we aim to propose a novel stemness-based classification approach to guide personalized clinical treatments, including immunotherapy.

METHODS

An integrative multi-omics analysis of PCA was performed to evaluate stemness-level heterogeneities. Unsupervised hierarchical clustering was used to classify PCAs based on stemness signature genes. To make stemness-based patient classification more clinically applicable, a stemness subtype predictor was jointly developed by using four PCA datasets and 76 machine learning algorithms.

RESULTS

We identified stemness signatures of PCA comprising 18 signaling pathways, by which we classified PCA samples into three stemness subtypes via unsupervised hierarchical clustering: low stemness (LS), medium stemness (MS), and high stemness (HS) subtypes. HS patients are sensitive to androgen deprivation therapy, taxanes, and immunotherapy and have the highest stemness, malignancy, tumor mutation load (TMB) levels, worst prognosis, and immunosuppression. LS patients are sensitive to platinum-based chemotherapy but resistant to immunotherapy and have the lowest stemness, malignancy, and TMB levels, best prognosis, and the highest immune infiltration. MS patients represent an intermediate status of stemness, malignancy, and TMB levels with a moderate prognosis. We further demonstrated that these three stemness subtypes are conserved across pan-tumor. Additionally, the 9-gene stemness subtype predictor we developed has a comparable capability to 18 signaling pathways to make tumor diagnosis and to predict tumor recurrence, metastasis, progression, prognosis, and efficacy of different treatments.

CONCLUSIONS

The three stemness subtypes we identified have the potential to be a powerful tool for clinical tumor molecular classification in PCA and pan-cancer, and to guide the selection of immunotherapy or other sensitive treatments for tumor patients.

Concordance and Clinical Significance of Genomic Alterations in Progressive Tumor Tissue and Matched Circulating Tumor DNA in Aggressive-variant Prostate Cancer

Sequencing of circulating tumor DNA (ctDNA) is a minimally invasive approach to reveal the genomic alterations of cancer; however, its comparison with sequencing of tumor tissue has not been well documented in real-world patients with aggressive-variant prostate cancer (AVPC). Concordance of genomic alterations was assessed between progressive tumor tissue and matched ctDNA by next-generation sequencing for 63 patients with AVPC. Associations of genomic alterations with progression-free survival (PFS) and overall survival (OS) were investigated using Kaplan-Meier and Cox regression analyses. A total of 161 somatic mutations (SMs) and 84 copy-number variants (CNVs) were detected in tumors, of which 97 were also found in ctDNA, giving concordance of 39.6% (97/245) across all SMs and CNVs, 49.7% for SMs only and 20.2% for CNVs only. Across all patients with AVPC, chemotherapy was associated with significantly longer median PFS (6 vs. 0.75 months, P = 0.001) and OS (11 vs. 8 months, P < 0.001) than next-generation hormonal therapy (NHT). Among types of chemotherapy, additional platinum-based chemotherapy was associated with significantly longer median PFS and OS than docetaxel only in patients with TP53, RB1, or PTEN alterations, and in those with ctDNA% ≥ 13.5%. The concordance analysis first provides evidence for combining the sequencing of ctDNA and tumor tissue in real-world patients with AVPC. Chemotherapy is associated with significantly better survival than NHT, and the benefit of additional platinum-based chemotherapy may depend on the presence of alterations in TP53, RB1, or PTEN and on a sufficiently high proportion of ctDNA in patients with AVPC.

SIGNIFICANCE

AVPC is a highly malignant and heterogeneous disease. Sequencing of ctDNA is a minimally invasive approach to reveal genomic alterations. On the basis of the current real-world study, we found ctDNA does not fully recapitulate the landscape of genomic alterations from progressive tumor tissue in AVPC. We also revealed AVPC can benefit from chemotherapy, especially platinum-based regimens. TP53/RB1/PTEN alterations in ctDNA or tumor tissue could be biomarkers for platinum-based chemotherapy in this setting.

Considerations and Approaches for Cancer Immunotherapy in the Aging Host

Advances in cancer immunotherapy are improving treatment successes in many distinct cancer types. Nonetheless, most tumors fail to respond. Age is the biggest risk for most cancers, and the median population age is rising worldwide. Advancing age is associated with manifold alterations in immune cell types, abundance, and functions, rather than simple declines in these metrics, the consequences of which remain incompletely defined. Our understanding of the effects of host age on immunotherapy mechanisms, efficacy, and adverse events remains incomplete. A deeper understanding of age effects in all these areas is required. Most cancer immunotherapy preclinical studies examine young subjects and fail to assess age contributions, a remarkable deficit given the known importance of age effects on immune cells and factors mediating cancer immune surveillance and immunotherapy efficacy. Notably, some cancer immunotherapies are more effective in aged versus young hosts, while others fail despite efficacy in the young. Here, we review our current understanding of age effects on immunity and associated nonimmune cells, the tumor microenvironment, cancer immunotherapy, and related adverse effects. We highlight important knowledge gaps and suggest areas for deeper enquiries, including in cancer immune surveillance, treatment response, adverse event outcomes, and their mitigation.

Genomic Profiling of Metastatic Castration-Resistant Prostate Cancer Samples Resistant to Androgen Receptor Pathway Inhibitors

PURPOSE

The androgen receptor axis inhibitors (ARPI; e.g., enzalutamide, abiraterone acetate) are administered in daily practice for men with metastatic castration-resistant prostate cancer (mCRPC). However, not all patients respond, and mechanisms of both primary and acquired resistance remain largely unknown.

EXPERIMENTAL DESIGN

In the prospective trial MATCH-R (NCT02517892), 59 patients with mCRPC underwent whole-exome sequencing (WES) and/or RNA sequencing (RNA-seq) of samples collected before starting ARPI. Also, 18 patients with mCRPC underwent biopsy at time of resistance. The objectives were to identify genomic alterations associated with resistance to ARPIs as well as to describe clonal evolution. Associations of genomic and transcriptomic alterations with primary resistance were determined using Wilcoxon and Fisher exact tests.

RESULTS

WES analysis indicated that no single-gene genomic alterations were strongly associated with primary resistance. RNA-seq analysis showed that androgen receptor (AR) gene alterations and expression levels were similar between responders and nonresponders. RNA-based pathway analysis found that patients with primary resistance had a higher Hedgehog pathway score, a lower AR pathway score and a lower NOTCH pathway score than patients with a response. Subclonal evolution and acquisition of new alterations in AR-related genes or neuroendocrine differentiation are associated with acquired resistance. ARPIs do not induce significant changes in the tumor transcriptome of most patients; however, programs associated with cell proliferation are enriched in resistant samples.

CONCLUSIONS

Low AR activity, activation of stemness programs, and Hedgehog pathway were associated with primary ARPIs' resistance, whereas most acquired resistance was associated with subclonal evolution, AR-related events, and neuroendocrine differentiation. See related commentary by Slovin, p. 4323.

Identification of tumor-agnostic biomarkers for predicting prostate cancer progression and biochemical recurrence

The diverse clinical outcomes of prostate cancer have led to the development of gene signature assays predicting disease progression. Improved prostate cancer progression biomarkers are needed as current RNA biomarker tests have varying success for intermediate prostate cancer. Interest grows in universal gene signatures for invasive carcinoma progression. Early breast and prostate cancers share characteristics, including hormone dependence and BRCA1/2 mutations. Given the similarities in the pathobiology of breast and prostate cancer, we utilized the NanoString BC360 panel, comprising the validated PAM50 classifier and pathway-specific signatures associated with general tumor progression as well as breast cancer-specific classifiers. This retrospective cohort of primary prostate cancers (n=53) was stratified according to biochemical recurrence (BCR) status and the CAPRA-S to identify genes related to high-risk disease. Two public cohort (TCGA-PRAD and GSE54460) were used to validate the results. Expression profiling of our cohort uncovered associations between PIP and INHBA with BCR and high CAPRA-S score, as well as associations between VCAN, SFRP2, and THBS4 and BCR. Despite low levels of the ESR1 gene compared to AR, we found strong expression of the ER signaling signature, suggesting that BCR may be driven by ER-mediated pathways. Kaplan-Meier and univariate Cox proportional hazards regression analysis indicated the expression of ESR1, PGR, VCAN, and SFRP2 could predict the occurrence of relapse events. This is in keeping with the pathways represented by these genes which contribute to angiogenesis and the epithelial-mesenchymal transition. It is likely that VCAN works by activating the stroma and remodeling the tumor microenvironment. Additionally, SFRP2 overexpression has been associated with increased tumor size and reduced survival rates in breast cancer and among prostate cancer patients who experienced BCR. ESR1 influences disease progression by activating stroma, stimulating stem/progenitor prostate cancer, and inducing TGF-β. Estrogen signaling may therefore serve as a surrogate to AR signaling during progression and in hormone-refractory disease, particularly in prostate cancer patients with stromal-rich tumors. Collectively, the use of agnostic biomarkers developed for breast cancer stratification has facilitated a precise clinical classification of patients undergoing radical prostatectomy and highlighted the therapeutic potential of targeting estrogen signaling in prostate cancer.

Regulation of SPDEF expression by DNA methylation in advanced prostate cancer

Introduction

Prostate cancer (PCa) presents a significant health challenge in men, with a substantial number of deaths attributed to metastatic castration resistant PCa (mCRPC). Moreover, African American men experience disproportionately high mortality rates due to PCa. This study delves into the pivotal role of SPDEF, a prostate specific Ets transcription factor, and its regulation by DNA methylation in the context of PCa progression.

Methods

We performed Epigenetic reprogramming using daily treatment with non-toxic dose of 5Aza-2-deoxycytidine (5Aza-dC) for two weeks to assess its impact on PDEF expression in prostate cancer cells. Next, we conducted functional studies on reprogrammed cells, including cell migration (wound-healing assay), invasion (Boyden-Chamber test), and proliferation (MTT assay) to comprehensively evaluate the consequences of altered PDEF expression. We used bisulfite sequencing (BSP) to examine DNA methylation at SPDEF promoter. Simultaneously, we utilized siRNA-mediated targeting of key DNMTs (DNMT1, DNMT3A, and DNMT3B) to elucidate their specific role in regulating PDEF. We measured mRNA and protein expressions using qRT-PCR and immune-blotting techniques, respectively.

Results

In this report, we observed that: a) there is a gradual decrease in SPDEF expression with a concomitant increase in methylated CpG sites within the SPDEF gene during prostate cancer progression from lower to higher Gleason grade; b) Expression of DNMT's (DNMT1, 3a and 3b) is increased during prostate cancer progression, and there is an inverse correlation between SPDEF and DNMT expression; c) SPDEF levels are decreased in RC77/T, a line of PCa cells from African American origin similar to PC3 and DU145 cells (CRPC cells), as compared to LNCaP cells , a line of androgen dependent cells,; d) the 5' CpG island of SPDEF gene are hypermethylated in SPDEF-negative CRPC ( PC3, DU145 and RC77/T) cell lines but the same regions are hypomethylated in SPDEF-positive castrate sensitive (LNCaP) cell line ; (e) expression of SPDEF in PCa cells lacking SPDEF decreases cell migration and invasion, but has no significant effect on cell proliferation, and; (f) treatment with the demethylating agent, 5-aza-2'-deoxycytidine, or silencing of the DNMT's by siRNA, partially restores SPDEF expression in SPDEF-negative PCa cell lines, and decreases cell migration and invasion.

Discussion

These results indicate hypermethylation is a prevalent mechanism for decreasing SPDEF expression during prostate cancer progression. The data demonstrate that loss of SPDEF expression in prostate cancer cells, a critical step in cellular plasticity, results from a potentially reversible process of aberrant DNA methylation. These studies suggest DMNT activity as a potential therapeutic vulnerability that can be exploited for limiting cellular plasticity, tumor progression, and therapy resistance in prostate cancer.

Epithelial specific splicing regulator proteins as emerging oncogenes in aggressive prostate cancer

Prostate cancer progression is connected to the activity of conventional oncogenes and tumour suppressors and driven by circulating steroid hormones. A key issue has been how to identify and care for aggressively developing prostate tumours. Here we discuss how expression of the splicing regulators ESRP1 and ESRP2, and how their role as "masterminds" of epithelial splicing patterns, have been identified as markers of aggressively proliferating prostate primary tumours. We suggest that the origin of prostate cancer within epithelial cells, and the subsequent association of ESRP1 and ESRP2 expression with more aggressive disease progression, identify ESRP1 and ESRP2 as lineage survival oncogenes. To move this field on in the future it will be important to identify the gene expression targets controlled by ESRP1/2 that regulate prostate cancer proliferation. Potential future therapies could be designed to target ESRP1 and ESRP2 protein activity or their regulated splice isoforms in aggressive prostate tumours. Design of these therapies is potentially complicated by the risk of producing a more mesenchymal splicing environment that might promote tumour metastasis.

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.

Biological and clinical implications of early-onset cancers: A unique subtype

In recent years, the incidence of cancers is continuously increasing in young adults. Early-onset cancer (EOC) is usually defined as patients with cancers under the age of 50, and may represent a unique subgroup due to its special disease features. Overall, EOCs often initiate at a young age, present as a better physical performance but high degree of malignancy. EOCs also share common epidemiological and hereditary risk factors. In this review, we discuss several representative EOCs which were well studied previously. By revealing their clinical and molecular similarities and differences, we consider the group of EOCs as a unique subtype compared to ordinary cancers. In consideration of EOC as a rising threat to human health, more researches on molecular mechanisms, and large-scale, prospective clinical trials should be carried out to further translate into improved outcomes.

Glycidamide-induced hypermutation in yeast single-stranded DNA reveals a ubiquitous clock-like mutational motif in humans

Mutagens often prefer specific nucleotides or oligonucleotide motifs that can be revealed by studying the hypermutation spectra in single-stranded (ss) DNA. We utilized a yeast model to explore mutagenesis by glycidamide, a simple epoxide formed endogenously in humans from the environmental toxicant acrylamide. Glycidamide caused ssDNA hypermutation in yeast predominantly in cytosines and adenines. The most frequent mutations in adenines occurred in the nAt→nGt trinucleotide motif. Base substitutions A→G in this motif relied on Rev1 translesion polymerase activity. Inactivating Rev1 did not alter the nAt trinucleotide preference, suggesting it may be an intrinsic specificity of the chemical reaction between glycidamide and adenine in the ssDNA. We found this mutational motif enriched in published sequencing data from glycidamide-treated mouse cells and ubiquitous in human cancers. In cancers, this motif was positively correlated with the single base substitution (SBS) smoking-associated SBS4 signature, with the clock-like signatures SBS1, SBS5, and was strongly correlated with smoking history and with age of tumor donors. Clock-like feature of the motif was also revealed in cells of human skin and brain. Given its pervasiveness, we propose that this mutational motif reflects mutagenic lesions to adenines in ssDNA from a potentially broad range of endogenous and exogenous agents.

Tissue-specific biological aging predicts progression in prostate cancer and acute myeloid leukemia

Introduction

Chronological aging is a well-recognized diagnostic and prognostic factor in multiple cancer types, yet the role of biological aging in manifesting cancer progression has not been fully explored yet.

Methods

Given the central role of chronological aging in prostate cancer and AML incidence, here we investigate a tissue-specific role of biological aging in prostate cancer and AML progression. We have employed Cox proportional hazards modeling to associate biological aging genes with cancer progression for patients from specific chronological aging groups and for patients with differences in initial cancer aggressiveness.

Results

Our prostate cancer-specific investigations nominated four biological aging genes (CD44, GADD45B, STAT3, GFAP) significantly associated with time to disease progression in prostate cancer in Taylor et al. patient cohort. Stratified survival analysis on Taylor dataset and validation on an independent TCGA and DKFZ PRAD patient cohorts demonstrated ability of these genes to predict prostate cancer progression, especially for patients with higher Gleason score and for patients younger than 60 years of age. We have further tested the generalizability of our approach and applied it to acute myeloid leukemia (AML). Our analysis nominated three AML-specific biological aging genes (CDC42EP2, CDC42, ALOX15B) significantly associated with time to AML overall survival, especially for patients with favorable cytogenetic risk score and for patients older than 56 years of age.

Discussion

Comparison of the identified PC and AML markers to genes selected at random and to known markers of progression demonstrated robustness of our results and nominated the identified biological aging genes as valuable markers of prostate cancer and AML progression, opening new avenues for personalized therapeutic management and potential novel treatment investigations.

Comprehensively analysis of splicing factors to construct prognosis prediction classifier in prostate cancer

Splicing factors (SFs) are proteins that control the alternative splicing (AS) of RNAs, which have been recognized as new cancer hallmarks. Their dysregulation has been found to be involved in many biological processes of cancer, such as carcinogenesis, proliferation, metastasis and senescence. Dysregulation of SFs has been demonstrated to contribute to the progression of prostate cancer (PCa). However, a comprehensive analysis of the prognosis value of SFs in PCa is limited. In this work, we systematically analysed 393 SFs to deeply characterize the expression patterns, clinical relevance and biological functions of SFs in PCa. We identified 53 survival-related SFs that can stratify PCa into two de nove molecular subtypes with distinct mRNA expression and AS-event expression patterns and displayed significant differences in pathway activity and clinical outcomes. An SF-based classifier was established using LASSO-COX regression with six key SFs (BCAS1, LSM3, DHX16, NOVA2, RBM47 and SNRPN), which showed promising prognosis-prediction performance with a receiver operating characteristic (ROC) >0.700 in both the training and testing datasets, as well as in three external PCa cohorts (DKFZ, GSE70769 and GSE21035). CRISPR/CAS9 screening data and cell-level functional analysis suggested that LSM3 and DHX16 are essential factors for the proliferation and cell cycle progression in PCa cells. This study proposes that SFs and AS events are potential multidimensional biomarkers for the diagnosis, prognosis and treatment of PCa.

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

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

SIGNIFICANCE

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

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.

Cancer-specific survival in patients with cholangiocarcinoma after radical surgery: a Novel, dynamic nomogram based on clinicopathological features and serum markers

BACKGROUND

This study aims to (1) identify preoperative testing-based characteristics associated with enhanced prognosis and survival for cholangiocarcinoma patients, and (2)create a distinctive nomogram to anticipate each patient's cancer-specific survival (CSS).

METHODS

Retrospective analysis was performed on 197 CCA patients who underwent radical surgery at Sun Yat-sen Memorial Hospital; they were divided into a 131-person "training cohort" and a 66-person "internal validation cohort." The prognostic nomogram was created following a preliminary Cox proportional hazard regression search for independent factors influencing the patients' CSS. Its applicable domain was examined via an external validation cohort, which included 235 patients from the Sun Yat-sen University Cancer Center.

RESULTS

The median follow-up period for the 131 patients in the training group was 49.3 months (range, 9.3 to 133.9 months). One-, three-, and five-year CSS rates were 68.7%, 24.5%, and 9.2%, respectively, with the median CSS length being 27.4 months (range: 1.4 to 125.2 months). PLT, CEA, AFP, tumor location, differentiation, lymph node metastasis, chemotherapy, and TNM stage were determined to be independent risk factors for CCA patients by univariate and multivariate Cox proportional hazard regression analysis. We were able to accurately predict postoperative CSS after incorporating all of these characteristics into a nomogram. The AJCC's 8th edition staging method's C-indices were statistically substantially (P < 0.001) lower than the nomogram's C-indices (0.84, 0.77, and 0.74 in the training, internal and external validation cohorts respectively).

CONCLUSIONS

A realistic and useful model for clinical decision-making and the optimization of therapy is presented as a nomogram that includes serum markers and clinicopathologic features for predicting postoperative survival in cholangiocarcinoma.

Aspartoacylase suppresses prostate cancer progression by blocking LYN activation

BACKGROUND

Globally, despite prostate cancer (PCa) representing second most prevalent malignancy in male, the precise molecular mechanisms implicated in its pathogenesis remain unclear. Consequently, elucidating the key molecular regulators that govern disease progression could substantially contribute to the establishment of novel therapeutic strategies, ultimately advancing the management of PCa.

METHODS

A total of 49 PCa tissues and 43 adjacent normal tissues were collected from January 2017 to December 2021 at Zhongnan Hospital of Wuhan University. The advanced transcriptomic methodologies were employed to identify differentially expressed mRNAs in PCa. The expression of aspartoacylase (ASPA) in PCa was thoroughly evaluated using quantitative real-time PCR and Western blotting techniques. To elucidate the inhibitory role of ASPA in PCa cell proliferation and metastasis, a comprehensive set of in vitro and in vivo assays were conducted, including orthotopic and tumor-bearing mouse models (n = 8 for each group). A combination of experimental approaches, such as Western blotting, luciferase assays, immunoprecipitation assays, mass spectrometry, glutathione S-transferase pull-down experiments, and rescue studies, were employed to investigate the underlying molecular mechanisms of ASPA's action in PCa. The Student's t-test was employed to assess the statistical significance between two distinct groups, while one-way analysis of variance was utilized for comparisons involving more than two groups. A two-sided P value of less than 0.05 was deemed to indicate statistical significance.

RESULTS

ASPA was identified as a novel inhibitor of PCa progression. The expression of ASPA was found to be significantly down-regulated in PCa tissue samples, and its decreased expression was independently associated with patients' prognosis (HR = 0.60, 95% CI 0.40-0.92, P = 0.018). Our experiments demonstrated that modulation of ASPA activity, either through gain- or loss-of-function, led to the suppression or enhancement of PCa cell proliferation, migration, and invasion, respectively. The inhibitory role of ASPA in PCa was further confirmed using orthotopic and tumor-bearing mouse models. Mechanistically, ASPA was shown to directly interact with the LYN and inhibit the phosphorylation of LYN as well as its downstream targets, JNK1/2 and C-Jun, in both PCa cells and mouse models, in an enzyme-independent manner. Importantly, the inhibition of LYN activation by bafetinib abrogated the promoting effect of ASPA knockdown on PCa progression in both in vitro and in vivo models. Moreover, we observed an inverse relationship between ASPA expression and LYN activity in clinical PCa samples, suggesting a potential regulatory role of ASPA in modulating LYN signaling.

CONCLUSION

Our findings provide novel insights into the tumor-suppressive function of ASPA in PCa and highlight its potential as a prognostic biomarker and therapeutic target for the management of this malignancy.

The DACH1 gene is frequently deleted in prostate cancer, restrains prostatic intraepithelial neoplasia, decreases DNA damage repair, and predicts therapy responses

Prostate cancer (PCa), the second leading cause of death in American men, includes distinct genetic subtypes with distinct therapeutic vulnerabilities. The DACH1 gene encodes a winged helix/Forkhead DNA-binding protein that competes for binding to FOXM1 sites. Herein, DACH1 gene deletion within the 13q21.31-q21.33 region occurs in up to 18% of human PCa and was associated with increased AR activity and poor prognosis. In prostate OncoMice, prostate-specific deletion of the Dach1 gene enhanced prostatic intraepithelial neoplasia (PIN), and was associated with increased TGFβ activity and DNA damage. Reduced Dach1 increased DNA damage in response to genotoxic stresses. DACH1 was recruited to sites of DNA damage, augmenting recruitment of Ku70/Ku80. Reduced Dach1 expression was associated with increased homology directed repair and resistance to PARP inhibitors and TGFβ kinase inhibitors. Reduced Dach1 expression may define a subclass of PCa that warrants specific therapies.

Recent advances in understanding DNA methylation of prostate cancer

Epigenetic modifications, such as DNA methylation, is widely studied in cancer. DNA methylation patterns have been shown to distinguish between benign and malignant tumors in various cancers, including prostate cancer. It may also contribute to oncogenesis, as it is frequently associated with downregulation of tumor suppressor genes. Aberrant patterns of DNA methylation, in particular the CpG island hypermethylator phenotype (CIMP), have shown associative evidence with distinct clinical features and outcomes, such as aggressive subtypes, higher Gleason score, prostate-specific antigen (PSA), and overall tumor stage, overall worse prognosis, as well as reduced survival. In prostate cancer, hypermethylation of specific genes is significantly different between tumor and normal tissues. Methylation patterns could distinguish between aggressive subtypes of prostate cancer, including neuroendocrine prostate cancer (NEPC) and castration resistant prostate adenocarcinoma. Further, DNA methylation is detectable in cell-free DNA (cfDNA) and is reflective of clinical outcome, making it a potential biomarker for prostate cancer. This review summarizes recent advances in understanding DNA methylation alterations in cancers with the focus on prostate cancer. We discuss the advanced methodology used for evaluating DNA methylation changes and the molecular regulators behind these changes. We also explore the clinical potential of DNA methylation as prostate cancer biomarkers and its potential for developing targeted treatment of CIMP subtype of prostate cancer.