Role of Alternative Splicing in Prostate Cancer Aggressiveness and Drug Resistance in African Americans

The Role of CENPK Splice Variant in Abiraterone Response in Metastatic Castration-Resistant Prostate Cancer

Most patients with metastatic prostate cancer eventually develop resistance to primary androgen deprivation therapy. To identify predictive biomarker for Abiraterone acetate/prednisone resistance, we screened alternative splice variants between responders and non-responders from the PROMOTE clinical study and pinned down the most significant variant, CENPK-delta8. Through preclinical patient-derived mouse xenograft (PDX) and 3D organoids obtained from responders and non-responders, as well as in vitro models, aberrant CENPK-delta8 expression was determined to link to drug resistance via enhanced migration and proliferation. The FLNA and FLOT1 were observed to specifically bind to CENK-delta8 rather than wild-type CENPK, underscoring the role of CENPK-delta8 in cytoskeleton organization and cell migration. Our study, leveraging data from the PROMOTE study, TCGA, and TCGA SpliceReq databases, highlights the important function of alternative splice variants in drug response and their potential to be prognostic biomarkers for improving individual therapeutic outcomes in precision medicine.

Aberrant PI3Kδ splice isoform as a potential biomarker and novel therapeutic target for endocrine cancers

Introduction

PI3K/AKT signaling pathway is upregulated in a broad spectrum of cancers. Among the class I PI3Ks (PI3Kδ/β/δ isoforms), PI3Kδ has been implicated in hematologic cancers and solid tumors. Alternative splicing is a post-transcriptional process for acquiring proteomic diversity in eukaryotic cells. Emerging evidence has highlighted the involvement of aberrant mRNA splicing in cancer development/progression.

Methods

Our previous studies revealed that PIK3CD-S is an oncogenic splice variant that promotes tumor aggressiveness and drug resistance in prostate cancer (PCa). To further evaluate the potential of utilizing PI3Kδ-S (encoded from PIK3CD-S) as a cancer biomarker and/or drug target, comprehensive analyses were performed in a series of patient samples and cell lines derived from endocrine/solid tumors. Specifically, IHC, immunofluorescence, western blot and RT-PCR assay results have demonstrated that PI3Kδ isoforms were highly expressed in endocrine/solid tumor patient specimens and cell lines.

Results

Differential PIK3CD-S/PIK3CD-L expression profiles were identified in a panel of endocrine/solid tumor cells. SiRNA knockdown of PIK3CD-L or PIK3CD-S differentially inhibits AKT/mTOR signaling in PCa, breast, colon and lung cancer cell lines. Moreover, siRNA knockdown of PTEN increased PI3Kδ levels and activated AKT/mTOR signaling, while overexpression of PTEN reduced PI3Kδ levels and inhibited AKT/mTOR signaling in cancer cells. Intriguingly, PI3Kδ-S levels remained unchanged upon either siRNA knockdown or overexpression of PTEN. Taken together, these results suggested that PTEN negatively regulates PI3Kδ-L and its downstream AKT/mTOR signaling, while PI3Kδ-S promotes AKT/mTOR signaling without regulation by PTEN. Lastly, PI3Kδ inhibitor Idelalisib and SRPK1/2 inhibitor SRPIN340 were employed to assess their efficacies on inhibiting the PI3Kδ-expressing endocrine/solid tumors. Our results have shown that Idelalisib effectively inhibited PI3Kδ-L (but not PI3Kδ-S) mediated AKT/mTOR signaling. In contrast, SRPIN340 reversed the aberrant mRNA splicing, thereby inhibiting AKT/mTOR signaling. In-vitro functional assays have further demonstrated that a combination of Idelalisib and SRPIN340 achieved a synergistic drug effect (with drastically reduced cell viabilities/growths of tumor spheroids) in inhibiting the advanced tumor cells.

Conclusion

In summary, our study has suggested a promising potential of utilizing PI3Kδ-S (an oncogenic isoform conferring drug resistance and exempt from PTEN regulation) as a prognostic biomarker and drug target in advanced endocrine cancers.

Novel, alternative splicing signature to detect lymph node metastasis in prostate adenocarcinoma with machine learning

Background

The presence of lymph node metastasis leads to a poor prognosis for prostate cancer (Pca). Recently, many studies have indicated that gene signatures may be able to predict the status of lymph nodes. The purpose of this study is to probe and validate a new tool to predict lymph node metastasis (LNM) based on alternative splicing (AS).

Methods

Gene expression profiles and clinical information of prostate adenocarcinoma cohort were retrieved from The Cancer Genome Atlas (TCGA) database, and the corresponding RNA-seq splicing events profiles were obtained from the TCGA SpliceSeq. Limma package was used to identify the differentially expressed alternative splicing (DEAS) events between LNM and non-LNM groups. Eight machine learning classifiers were built to train with stratified five-fold cross-validation. SHAP values was used to explain the model.

Results

333 differentially expressed alternative splicing (DEAS) events were identified. Using correlation filter and the least absolute shrinkage and selection operator (LASSO) method, a 96 AS signature was identified that had favorable discrimination in the training set and validated in the validation set. The linear discriminant analysis (LDA) was the best classifier after 100 iterations of training. The LDA classifier was able to distinguish between LNM and non-LNM with an area under the receiver operating curve of 0.962 ± 0.026 in the training set (D1 = 351) and 0.953 in the validation set (D2 = 62). The decision curve analysis plot proved the clinical application of the AS-based model.

Conclusion

Machine learning combined with AS data could robustly distinguish between LNM and non-LNM in Pca.

Identification of bicalutamide resistance-related genes and prognosis prediction in patients with prostate cancer

Background

Prostate cancer (PCa) is the second most common type of cancer and the fifth leading cause of cancer-related death in men. Androgen deprivation therapy (ADT) has become the first-line therapy for inhibiting PCa progression; however, nearly all patients receiving ADT eventually progress to castrate-resistant prostate cancer. Therefore, this study aimed to identify hub genes related to bicalutamide resistance in PCa and provide new insights into endocrine therapy resistance.

Methods

The data were obtained from public databases. Weighted correlation network analysis was used to identify the gene modules related to bicalutamide resistance, and the relationship between the samples and disease-free survival was analyzed. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed, and hub genes were identified. The LASSO algorithm was used to develop a bicalutamide resistance prognostic model in patients with PCa, which was then verified. Finally, we analyzed the tumor mutational heterogeneity and immune microenvironment in both groups.

Results

Two drug resistance gene modules were identified. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses revealed that both modules are involved in RNA splicing. The protein-protein interaction network identified 10 hub genes in the brown module LUC7L3, SNRNP70, PRPF3, LUC7L, CLASRP, CLK1, CLK2, U2AF1L4, NXF1, and THOC1) and 13 in the yellow module (PNN, PPWD1, SRRM2, DHX35, DMTF1, SALL4, MTA1, HDAC7, PHC1, ACIN1, HNRNPH1, DDX17, and HDAC6). The prognostic model composed of RNF207, REC8, DFNB59, HOXA2, EPOR, PILRB, LSMEM1, TCIRG1, ABTB1, ZNF276, ZNF540, and DPY19L2 could effectively predict patient prognosis. Genomic analysis revealed that the high- and low-risk groups had different mutation maps. Immune infiltration analysis showed a statistically significant difference in immune infiltration between the high- and low-risk groups, and that the high-risk group may benefit from immunotherapy.

Conclusion

In this study, bicalutamide resistance genes and hub genes were identified in PCa, a risk model for predicting the prognosis of patients with PCa was constructed, and the tumor mutation heterogeneity and immune infiltration in high- and low-risk groups were analyzed. These findings offer new insights into ADT resistance targets and prognostic prediction in patients with PCa.

Prostate Cancer Disparities and Management in Southern Africa: Insights into Practices, Norms and Values

Prostate cancer (PCa) is a leading cause of mortality in men of African origin. While men of African descent in high-income countries (HICs) demonstrate poor prognosis compared to their European counterparts, African men on the African continent, particularly Southern Africa have shown even higher PCa mortality rates. Extrinsic factors such as the socioeconomic status, education level, income level, geographic location and race contribute to PCa patient outcome. These are further deepened by the African norms which are highly esteemed and may have detrimental effects on PCa patients' health. Insights into African cultures and social constructs have been identified as key elements towards improving men's health care seeking behaviour which will in turn improve PCa patients' outcome. Compared to Southern Africa, the Eastern, Western and Central African regions have lower PCa incidence rates but higher mortality rates. The availability of cancer medical equipment has also been reported to be disproportionate in Africa, with most cancer resources in Northern and Southern Africa. Even within Southern Africa, cancer management resources are unevenly available where one country must access PCa specialised care in the neighbouring countries. While PCa seems to be better managed in HICs, steps towards effective PCa management are urgently needed in Africa, as this continent represents a significant portion of low-middle-income countries (LMICs). Replacing African men in Africa with African American men may not optimally resolve PCa challenges in Africa. Adopting western PCa management practices can be optimised by integrating improved core-African norms. The aim of this review is to discuss PCa disparities in Africa, deliberate on the significance of integrating African norms around masculinity and discuss challenges and opportunities towards effective PCa care in Africa, particularly in Southern Africa.

Gene expression analysis reveals a 5-gene signature for progression-free survival in prostate cancer

Prostate cancer (PCa) is the second most common male cancer worldwide, but effective biomarkers for the presence or progression risk of disease are currently elusive. In a series of nine matched histologically confirmed PCa and benign samples, we carried out an integrated transcriptome-wide gene expression analysis, including differential gene expression analysis and weighted gene co-expression network analysis (WGCNA), which identified a set of potential gene markers highly associated with tumour status (malignant vs. benign). We then used these genes to establish a minimal progression-free survival (PFS)-associated gene signature (GS) (PCBP1, PABPN1, PTPRF, DANCR, and MYC) using least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox regression analyses from The Cancer Genome Atlas prostate adenocarcinoma (TCGA-PRAD) dataset. Our signature was able to predict PFS over 1, 3, and 5 years in TCGA-PRAD dataset, with area under the curve (AUC) of 0.64–0.78, and our signature remained as a prognostic factor independent of age, Gleason score, and pathological T and N stages. A nomogram combining the signature and Gleason score demonstrated improved predictive capability for PFS (AUC: 0.71–0.85) and was superior to the Cambridge Prognostic Group (CPG) model alone and some conventionally used clinicopathological factors in predicting PFS. In conclusion, we have identified and validated a novel five-gene signature and established a nomogram that effectively predicted PFS in patients with PCa. Findings may improve current prognosis tools for PFS and contribute to clinical decision-making in PCa treatment.

A repositioning screen using an FGFR2 splicing reporter reveals compounds that regulate epithelial-mesenchymal transitions and inhibit growth of prostate cancer xenografts

Research in the area of hallmarks of cancer has opened the possibility of designing new therapies based on modulating these cancer properties. We present here a screen designed to find chemicals that modulate epithelial-mesenchymal transitions (EMTs) in prostate cancer. For screening, we used a repurposing library and, as a readout, an FGFR2-based splicing reporter, which has been shown previously to be a sensor for EMTs. Various properties of cancer cells were assessed, signaling pathways investigated, and in vivo experiments in nude mice xenografts performed. The screen yielded three hit compounds (a T-type Ca channel inhibitor, an L-type Ca channel inhibitor, and an opioid antagonist) that switch FGFR2 splicing and induce an epithelial phenotype in prostate cancer cells. The compounds affected differently various properties of cancer cells, but all of them decreased cell migration, which is in line with modulating EMTs. We further present mechanistic insights into one of the compounds, nemadipine-A. The administration of nemadipine-A intraperitoneally in a nude mouse xenograft model of prostate cancer slowed tumor growth. To conclude, we show that knowledge of the molecular mechanisms that connect alternative splicing and various cancer properties may be used as a platform for drug development.

Alternative Splicing-Based Differences Between Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma: Genes, Immune Microenvironment, and Survival Prognosis

Alternative splicing (AS) event is a novel biomarker of tumor tumorigenesis and progression. However, the comprehensive analysis of hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC) is lacking. Differentially expressed analysis was used to identify the differentially expressed alternative splicing (DEAS) events between HCC or ICC tissues and their normal tissues. The correlation between DEAS events and functional analyses or immune features was evaluated. The cluster analysis based on DEAS can accurately reflect the differences in the immune microenvironment between HCC and ICC. Forty-five immune checkpoints and 23 immune features were considered statistically significant in HCC, while only seven immune checkpoints and one immune feature in ICC. Then, the prognostic value of DEAS events was studied, and two transcripts with different basic cell functions (proliferation, cell cycle, invasion, and migration) were produced by ADHFE1 through alternative splicing. Moreover, four nomograms were established in conjunction with relevant clinicopathological factors. Finally, we found two most significant splicing factors and further showed their protein crystal structure. The joint analysis of the AS events in HCC and ICC revealed novel insights into immune features and clinical prognosis, which might provide positive implications in HCC and ICC treatment.

Identification of prognostic alternative splicing events in sarcoma

Sarcoma is a rare malignancy with unfavorable prognoses. Accumulating evidence indicates that aberrant alternative splicing (AS) events are generally involved in cancer pathogenesis. The aim of this study was to identify the prognostic value of AS-related survival genes as potential biomarkers, and highlight the functional roles of AS events in sarcoma. RNA-sequencing and AS-event datasets were downloaded from The Cancer Genome Atlas (TCGA) sarcoma cohort and TCGA SpliceSeq, respectively. Survival-related AS events were further assessed using a univariate analysis. A multivariate Cox regression analysis was also performed to establish a survival-gene signature to predict patient survival, and the area-under-the-curve method was used to evaluate prognostic reliability. KOBAS 3.0 and Cytoscape were used to functionally annotate AS-related genes and to assess their network interactions. We detected 9674 AS events in 40,184 genes from 236 sarcoma samples, and the 15 most significant genes were then used to construct a survival regression model. We further validated the involvement of ten potential survival-related genes (TUBB3, TRIM69, ZNFX1, VAV1, KCNN2, VGLL3, AK7, ARMC4, LRRC1, and CRIP1) in the occurrence and development of sarcoma. Multivariate survival model analyses were also performed, and validated that a model using these ten genes provided good classifications for predicting patient outcomes. The present study has increased our understanding of AS events in sarcoma, and the gene-based model using AS-related events may serve as a potential predictor to determine the survival of sarcoma patients.

Identification and Characterization of Alternatively Spliced Transcript Isoforms of IRX4 in Prostate Cancer

Alternative splicing (AS) is tightly regulated to maintain genomic stability in humans. However, tumor growth, metastasis and therapy resistance benefit from aberrant RNA splicing. Iroquois-class homeodomain protein 4 (IRX4) is a TALE homeobox transcription factor which has been implicated in prostate cancer (PCa) as a tumor suppressor through genome-wide association studies (GWAS) and functional follow-up studies. In the current study, we characterized 12 IRX4 transcripts in PCa cell lines, including seven novel transcripts by RT-PCR and sequencing. They demonstrate unique expression profiles between androgen-responsive and nonresponsive cell lines. These transcripts were significantly overexpressed in PCa cell lines and the cancer genome atlas program (TCGA) PCa clinical specimens, suggesting their probable involvement in PCa progression. Moreover, a PCa risk-associated SNP rs12653946 genotype GG was corelated with lower IRX4 transcript levels. Using mass spectrometry analysis, we identified two IRX4 protein isoforms (54.4 kDa, 57 kDa) comprising all the functional domains and two novel isoforms (40 kDa, 8.7 kDa) lacking functional domains. These IRX4 isoforms might induce distinct functional programming that could contribute to PCa hallmarks, thus providing novel insights into diagnostic, prognostic and therapeutic significance in PCa management.

Prostate cancer racial, socioeconomic, geographic disparities: targeting the genomic landscape and splicing events in search for diagnostic, prognostic and therapeutic targets

Prostate cancer (PCa) is one of the leading causes of deaths in men globally. This is a heterogeneous and complex disease that urgently warrants further insight into its pathology. Developed countries have thus far the highest PCa incidence rates, with comparatively low mortality rates. Even though PCa in the Asian population seems to have high incidence and mortality rates, the African countries are emerging as the focal center for this disease. It has also been reported that the Sub-Saharan (SSA) countries have both the highest incidence and mortality rates. To date, few studies have reported the link between PCa and African populations. Adequate evidence is still missing to fully comprehend this relationship. While it has been brought to attention that racial, geographical and socioeconomic status are contributing factors, men of African descent across the globe, irrespective of their geographical position have higher PCa incidence and mortality rates compared to their white counterparts. To date, hormone therapy is the mainstay treatment of PCa, while the dysregulation of androgen receptor (AR) signaling is a hallmark of PCa. One of the emerging problems with this therapeutic approach is resistance to antiandrogens, and that AR splice isoforms implicated in the progression of PCa lack the therapeutic ligand-binding domain (LBD) target. AR splice variants targeted therapy is emerging and in clinical trials. Leveraging PCa transcriptomics is key towards PCa precision medicine. The aim of this review is to outline the PCa epidemiology globally and in Africa, PCa associated risk factors, discuss AR signaling and PCa mechanisms, the role of dysregulated splicing in PCa as novel prognostic indicators and therapeutic targets.

Nanosystem functionalization strategies for prostate cancer treatment: a review

Prostate cancer (PC) has a high morbidity and mortality rate worldwide, and the current clinical guidelines can vary depending on the stage of the disease. Drug delivery nanosystems (DDNs) can improve biopharmaceutical properties of encapsulated anti-cancer drugs by modulating their release kinetics, improving physicochemical stability and reducing toxicity. DDN can also enhance the ability of specific targeting through surface modification by coupling ligands (antibodies, nucleic acids, peptides, aptamer, proteins), thus favouring the cell internalisation process by endocytosis. The purposes of this review are to describe the limitations in the treatment of PC, explore different functionalization such as polymeric, lipid and inorganic nanosystems aimed at the treatment of PC, and demonstrate the improvement of this modification for an active target, as alternative and promising candidates for new therapies.

ESRP1 regulates alternative splicing of CARM1 to sensitize small cell lung cancer cells to chemotherapy by inhibiting TGF-β/Smad signaling

Epithelial splicing regulatory protein 1 (ESRP1) is an RNA-binding protein that regulates alternative splicing of mRNA. ESRP1 plays an important role in chemoresistance of various cancers, including breast cancer, colon cancer and non-small cell lung cancer. However, the role of ESRP1 and its mechanism in small cell lung cancer (SCLC) chemoresistance remains unclear. In this study, we found that ESRP1 is significantly downregulated in SCLC chemo-resistant cells compared with chemo-sensitive cells. Moreover, the expression of ESRP1 was significantly lower in SCLC tissues than that in normal adjacent tissues and positively correlated with overall survival. Overexpression of ESRP1 increased SCLC chemosensitivity, and induced cell apoptosis and cell cycle arrest, whereas knockdown of ESRP1 induced the opposite effects. ESRP1 could inhibit the growth of SCLC in vivo. Through mRNA transcriptome sequencing, we found that ESRP1 regulates coactivator-associated arginine methyltransferase 1 (CARM1) to produce two different transcripts CARM1FL and CARM1ΔE15 by alternative splicing. ESRP1 affects the chemoresistance of SCLC by changing the content of different transcripts of CARM1. Furthermore, CARM1 regulates arginine methylation of Smad7, activates the TGF-β/Smad pathway and induces epithelial-to-mesenchymal transition (EMT), thereby promoting SCLC chemoresistance. Collectively, our study firstly demonstrates that ESRP1 inhibits the TGF-β/Smad signaling pathway by regulating alternative splicing of CARM1, thereby reversing chemoresistance of SCLC. The splicing factor ESRP1 may serve as a new drug resistance marker molecule and a potential therapeutic target in SCLC patients.

Psychosocial Stress, Glucocorticoid Signaling, and Prostate Cancer Health Disparities in African American Men

Recent advances in our understanding of racial disparities in prostate cancer (PCa) incidence and mortality that disproportionately affect African American (AA) men have provided important insights into the psychosocial, socioeconomic, environmental, and molecular contributors. There is, however, limited mechanistic knowledge of how the interplay between these determinants influences prostate tumor aggressiveness in AA men and other men of African ancestry. Growing evidence indicates that chronic psychosocial stress in AA populations leads to sustained glucocorticoid signaling through the glucocorticoid receptor (GR), with negative physiological and pathological consequences. Compelling evidence indicates that treatment of castration-resistant prostate cancer (CRPC) with anti-androgen therapy activates GR signaling. This enhanced GR signaling bypasses androgen receptor (AR) signaling and transcriptionally activates both AR-target genes and GR-target genes, resulting in increased prostate tumor resistance to anti-androgen therapy, chemotherapy, and radiotherapy. Given its enhanced signaling in AA men, GR-together with specific genetic drivers-may promote CRPC progression and exacerbate tumor aggressiveness in this population, potentially contributing to PCa mortality disparities. Ongoing and future CRPC clinical trials that combine standard of care therapies with GR modulators should assess racial differences in therapy response and clinical outcomes in order to improve PCa health disparities that continue to exist for AA men.