Antagonism of B cell enhancer networks by STAT5 drives leukemia and poor patient survival.

The transcription factor STAT5 has a critical role in B cell acute lymphoblastic leukemia (B-ALL). How STAT5 mediates this effect is unclear. Here we found that activation of STAT5 worked together with defects in signaling components of the precursor to the B cell antigen receptor (pre-BCR), including defects in BLNK, BTK, PKCß, NF-κB1 and IKAROS, to initiate B-ALL. STAT5 antagonized the transcription factors NF-κB and IKAROS by opposing regulation of shared target genes. Super-enhancers showed enrichment for STAT5 binding and were associated with an opposing network of transcription factors, including PAX5, EBF1, PU.1, IRF4 and IKAROS. Patients with a high ratio of active STAT5 to NF-κB or IKAROS had more-aggressive disease. Our studies indicate that an imbalance of two opposing transcriptional programs drives B-ALL and suggest that restoring the balance of these pathways might inhibit B-ALL.

A pan-cancer transcriptome analysis of exitron splicing identifies novel cancer driver genes and neoepitopes.

Exitron splicing (EIS) creates a cryptic intron (called an exitron) within a protein-coding exon to increase proteome diversity. EIS is poorly characterized, but emerging evidence suggests a role for EIS in cancer. Through a systematic investigation of EIS across 33 cancers from 9,599 tumor transcriptomes, we discovered that EIS affected 63% of human coding genes and that 95% of those events were tumor specific. Notably, we observed a mutually exclusive pattern between EIS and somatic mutations in their affected genes. Functionally, we discovered that EIS altered known and novel cancer driver genes for causing gain- or loss-of-function, which promotes tumor progression. Importantly, we identified EIS-derived neoepitopes that bind to major histocompatibility complex (MHC) class I or II. Analysis of clinical data from a clear cell renal cell carcinoma cohort revealed an association between EIS-derived neoantigen load and checkpoint inhibitor response. Our findings establish the importance of considering EIS alterations when nominating cancer driver events and neoantigens.

Interleukin-15 Complex Treatment Protects Mice from Cerebral Malaria by Inducing Interleukin-10-Producing Natural Killer Cells.

Cerebral malaria is a deadly complication of Plasmodium infection and involves blood brain barrier (BBB) disruption following infiltration of white blood cells. During experimental cerebral malaria (ECM), mice inoculated with Plasmodium berghei ANKA-infected red blood cells develop a fatal CM-like disease caused by CD8+ T cell-mediated pathology. We found that treatment with interleukin-15 complex (IL-15C) prevented ECM, whereas IL-2C treatment had no effect. IL-15C-expanded natural killer (NK) cells were necessary and sufficient for protection against ECM. IL-15C treatment also decreased CD8+ T cell activation in the brain and prevented BBB breakdown without influencing parasite load. IL-15C induced NK cells to express IL-10, which was required for IL-15C-mediated protection against ECM. Finally, we show that ALT-803, a modified human IL-15C, mediates similar induction of IL-10 in NK cells and protection against ECM. These data identify a regulatory role for cytokine-stimulated NK cells in the prevention of a pathogenic immune response.

PxBLAT: an efficient python binding library for BLAT.

BACKGROUND: With the surge in genomic data driven by advancements in sequencing technologies, the demand for efficient bioinformatics tools for sequence analysis has become paramount. BLAST-like alignment tool (BLAT), a sequence alignment tool, faces limitations in performance efficiency and integration with modern programming environments, particularly Python. This study introduces PxBLAT, a Python-based framework designed to enhance the capabilities of BLAT, focusing on usability, computational efficiency, and seamless integration within the Python ecosystem. RESULTS: PxBLAT demonstrates significant improvements over BLAT in execution speed and data handling, as evidenced by comprehensive benchmarks conducted across various sample groups ranging from 50 to 600 samples. These experiments highlight a notable speedup, reducing execution time compared to BLAT. The framework also introduces user-friendly features such as improved server management, data conversion utilities, and shell completion, enhancing the overall user experience. Additionally, the provision of extensive documentation and comprehensive testing supports community engagement and facilitates the adoption of PxBLAT. CONCLUSIONS: PxBLAT stands out as a robust alternative to BLAT, offering performance and user interaction enhancements. Its development underscores the potential for modern programming languages to improve bioinformatics tools, aligning with the needs of contemporary genomic research. By providing a more efficient, user-friendly tool, PxBLAT has the potential to impact genomic data analysis workflows, supporting faster and more accurate sequence analysis in a Python environment.

ScanNeo2: a comprehensive workflow for neoantigen detection and immunogenicity prediction from diverse genomic and transcriptomic alterations.

MOTIVATION: Neoantigens, tumor-specific protein fragments, are invaluable in cancer immunotherapy due to their ability to serve as targets for the immune system. Computational prediction of these neoantigens from sequencing data often requires multiple algorithms and sophisticated workflows, which are currently restricted to specific types of variants, such as single-nucleotide variants or insertions/deletions. Nevertheless, other sources of neoantigens are often overlooked. RESULTS: We introduce ScanNeo2 an improved and fully automated bioinformatics pipeline designed for high-throughput neoantigen prediction from raw sequencing data. Unlike its predecessor, ScanNeo2 integrates multiple sources of somatic variants, including canonical- and exitron-splicing, gene fusion events, and various somatic variants. Our benchmark results demonstrate that ScanNeo2 accurately identifies neoantigens, providing a comprehensive and more efficient solution for neoantigen prediction. AVAILABILITY AND IMPLEMENTATION: ScanNeo2 is freely available at https://github.com/ylab-hi/ScanNeo2/ and is accompanied by instruction and application data.

ScanExitronLR: characterization and quantification of exitron splicing events in long-read RNA-seq data.

SUMMARY: Exitron splicing is a type of alternative splicing where coding sequences are spliced out. Recently, exitron splicing has been shown to increase proteome plasticity and play a role in cancer. Long-read RNA-seq is well suited for quantification and discovery of alternative splicing events; however, there are currently no tools available for the detection and annotation of exitrons in long-read RNA-seq data. Here, we present ScanExitronLR, an application for the characterization and quantification of exitron splicing events in long-reads. From a BAM alignment file, reference genome and reference gene annotation, ScanExitronLR outputs exitron events at the individual transcript level. Outputs of ScanExitronLR can be used in downstream analyses of differential exitron splicing. In addition, ScanExitronLR optionally reports exitron annotations such as truncation or frameshift type, nonsense-mediated decay status and Pfam domain interruptions. We demonstrate that ScanExitronLR performs better on noisy long-reads than currently published exitron detection algorithms designed for short-read data. AVAILABILITY AND IMPLEMENTATION: ScanExitronLR is freely available at https://github.com/ylab-hi/ScanExitronLR and distributed as a pip package on the Python Package Index. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Histone Deacetylase Sirtuin 1 Promotes Loss of Primary Cilia in Cholangiocarcinoma.

BACKGROUND AND AIMS: Sirtuin 1 (SIRT1) is a complex NAD+ -dependent protein deacetylase known to act as a tumor promoter or suppressor in different cancers. Here, we describe a mechanism of SIRT1-induced destabilization of primary cilia in cholangiocarcinoma (CCA). APPROACH AND RESULTS: A significant overexpression of SIRT1 was detected in human CCA specimens and CCA cells including HuCCT1, KMCH, and WITT1 as compared with normal cholangiocytes (H69 and NHC). Small interfering RNA (siRNA)-mediated knockdown of SIRT1 in HuCCT1 cells induced cilia formation, whereas overexpression of SIRT1 in normal cholangiocytes suppressed ciliary expression. Activity of SIRT1 was regulated by presence of NAD+ in CCA cells. Inhibition of NAD -producing enzyme nicotinamide phosphoribosyl transferase increased ciliary length and frequency in CCA cells and in SIRT1-overexpressed H69 cells. Furthermore, we also noted that SIRT1 induces the proteasomal mediated degradation of ciliary proteins, including α-tubulin, ARL13B, and KIF3A. Moreover, overexpression of SIRT1 in H69 and NHC cells significantly induced cell proliferation and, conversely, SIRT1 inhibition in HuCCT1 and KMCH cells using siRNA or sirtinol reduced cell proliferation. In an orthotopic transplantation rat CCA model, the SIRT1 inhibitor sirtinol reduced tumor size and tumorigenic proteins (glioma-associated oncogene 1, phosphorylated extracellular signal-regulated kinase, and IL-6) expression. CONCLUSIONS: In conclusion, these results reveal the tumorigenic role of SIRT1 through modulation of primary cilia formation and provide the rationale for developing therapeutic approaches for CCA using SIRT1 as a target.

RAS internal tandem duplication disrupts GTPase-activating protein (GAP) binding to activate oncogenic signaling.

The oncogene RAS is one of the most widely studied proteins in cancer biology, and mutant active RAS is a driver in many types of solid tumors and hematological malignancies. Yet the biological effects of different RAS mutations and the tissue-specific clinical implications are complex and nuanced. Here, we identified an internal tandem duplication (ITD) in the switch II domain of NRAS from a patient with extremely aggressive colorectal carcinoma. Results of whole-exome DNA sequencing of primary and metastatic tumors indicated that this mutation was present in all analyzed metastases and excluded the presence of any other clear oncogenic driver mutations. Biochemical analysis revealed increased interaction of the RAS ITD with Raf proto-oncogene Ser/Thr kinase (RAF), leading to increased phosphorylation of downstream MAPK/ERK kinase (MEK)/extracellular signal-regulated kinase (ERK). The ITD prevented interaction with neurofibromin 1 (NF1)-GTPase-activating protein (GAP), providing a mechanism for sustained activity of the RAS ITD protein. We present the first crystal structures of NRAS and KRAS ITD at 1.65-1.75 Å resolution, respectively, providing insight into the physical interactions of this class of RAS variants with its regulatory and effector proteins. Our in-depth bedside-to-bench analysis uncovers the molecular mechanism underlying a case of highly aggressive colorectal cancer and illustrates the importance of robust biochemical and biophysical approaches in the implementation of individualized medicine.

LncGSEA: a versatile tool to infer lncRNA associated pathways from large-scale cancer transcriptome sequencing data.

BACKGROUND: Long non-coding RNAs (lncRNAs) are a growing focus in cancer research. Deciphering pathways influenced by lncRNAs is important to understand their role in cancer. Although knock-down or overexpression of lncRNAs followed by gene expression profiling in cancer cell lines are established approaches to address this problem, these experimental data are not available for a majority of the annotated lncRNAs. RESULTS: As a surrogate, we present lncGSEA, a convenient tool to predict the lncRNA associated pathways through Gene Set Enrichment Analysis of gene expression profiles from large-scale cancer patient samples. We demonstrate that lncGSEA is able to recapitulate lncRNA associated pathways supported by literature and experimental validations in multiple cancer types. CONCLUSIONS: LncGSEA allows researchers to infer lncRNA regulatory pathways directly from clinical samples in oncology. LncGSEA is written in R, and is freely accessible at https://github.com/ylab-hi/lncGSEA .

Impaired replication elongation in Tetrahymena mutants deficient in histone H3 Lys 27 monomethylation.

Replication of nuclear DNA occurs in the context of chromatin and is influenced by histone modifications. In the ciliate Tetrahymena thermophila, we identified TXR1, encoding a histone methyltransferase. TXR1 deletion resulted in severe DNA replication stress, manifested by the accumulation of ssDNA, production of aberrant replication intermediates, and activation of robust DNA damage responses. Paired-end Illumina sequencing of ssDNA revealed intergenic regions, including replication origins, as hot spots for replication stress in ΔTXR1 cells. ΔTXR1 cells showed a deficiency in histone H3 Lys 27 monomethylation (H3K27me1), while ΔEZL2 cells, deleting a Drosophila E(z) homolog, were deficient in H3K27 di- and trimethylation, with no detectable replication stress. A point mutation in histone H3 at Lys 27 (H3 K27Q) mirrored the phenotype of ΔTXR1, corroborating H3K27me1 as a key player in DNA replication. Additionally, we demonstrated interactions between TXR1 and proliferating cell nuclear antigen (PCNA). These findings support a conserved pathway through which H3K27me1 facilitates replication elongation.

ASCL1-regulated DARPP-32 and t-DARPP stimulate small cell lung cancer growth and neuroendocrine tumour cell proliferation.

BACKGROUND: Small cell lung cancer (SCLC) is the most aggressive form of lung cancer, and new molecular insights are necessary for prognostic and therapeutic advances. METHODS: Dopamine and cAMP-regulated phosphoprotein, Mr 32000 (DARPP-32) and its N-terminally truncated splice variant, t-DARPP, were stably overexpressed or ablated in human DMS-53 and H1048 SCLC cells. Functional assays and immunoblotting were used to assess how DARPP-32 isoforms regulate SCLC cell growth, proliferation, and apoptosis. DARPP-32-modulated SCLC cells were orthotopically injected into the lungs of SCID mice to evaluate how DARPP-32 and t-DARPP regulate neuroendocrine tumour growth. Immunostaining for DARPP-32 proteins was performed in SCLC patient-derived specimens. Bioinformatics analysis and subsequent transcription assays were used to determine the mechanistic basis of DARPP-32-regulated SCLC growth. RESULTS: We demonstrate in mice that DARPP-32 and t-DARPP promote SCLC growth through increased Akt/Erk-mediated proliferation and anti-apoptotic signalling. DARPP-32 isoforms are overexpressed in SCLC patient-derived tumour tissue, but undetectable in physiologically normal lung. Achaete-scute homologue 1 (ASCL1) transcriptionally activates DARPP-32 isoforms in human SCLC cells. CONCLUSIONS: We reveal new regulatory mechanisms of SCLC oncogenesis that suggest DARPP-32 isoforms may represent a negative prognostic indicator for SCLC and serve as a potential target for the development of new therapies.

ScanNeo: identifying indel-derived neoantigens using RNA-Seq data.

SUMMARY: Insertion and deletion (indels) have been recognized as an important source generating tumor-specific mutant peptides (neoantigens). The focus of indel-derived neoantigen identification has been on leveraging DNA sequencing such as whole exome sequencing, with the effort of using RNA-seq less well explored. Here we present ScanNeo, a fast-streamlined computational pipeline for analyzing RNA-seq to predict neoepitopes derived from small to large-sized indels. We applied ScanNeo in a prostate cancer cell line and validated our predictions with matched mass spectrometry data. Finally, we demonstrated that indel neoantigens predicted from RNA-seq were associated with checkpoint inhibitor response in a cohort of melanoma patients. AVAILABILITY AND IMPLEMENTATION: ScanNeo is implemented in Python. It is freely accessible at the GitHub repository (https://github.com/ylab-hi/ScanNeo). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

p300 Acetyltransferase Is a Cytoplasm-to-Nucleus Shuttle for SMAD2/3 and TAZ Nuclear Transport in Transforming Growth Factor ß-Stimulated Hepatic Stellate Cells.

Nuclear translocation of mothers against decapentaplegic homolog 2/3 (SMAD2/3), core transcription factors of transforming growth factor ß (TGF-ß) signaling, is critical for hepatic stellate cell (HSC) differentiation into metastasis-promoting myofibroblasts. SMAD2/3 have multiple coactivators, including WW domain-containing transcription regulator protein 1 (WWTR1 or TAZ) and p300 acetyltransferase. In the nucleus, TAZ binds to SMAD2/3 to prevent SMAD2/3 nuclear export. However, how TAZ and SMAD2/3 enter the nucleus remains poorly understood because neither contains a nuclear localization signal (NLS), an amino acid sequence tagging proteins for nuclear transport. p300 is an NLS-containing large scaffold protein, so we hypothesized that SMAD2/3 and TAZ may undergo nuclear import through complexing with p300. Coimmunoprecipitation, immunofluorescence, and nuclear fractionation assays revealed that TGF-ß1 promoted binding of SMAD2/3 and TAZ to p300 and that p300 inactivation disrupted TGF-ß1-mediated SMAD2/3 and TAZ nuclear accumulation. Deleting the p300 NLS blocked TGF-ß1-induced SMAD2/3 and TAZ nuclear transport. Consistently, p300 inactivation suppressed TGF-ß1-mediated HSC activation and transcription of genes encoding tumor-promoting factors, such as connective tissue growth factor, Tenascin C, Periostin, platelet-derived growth factor C, and fibroblast growth factor 2, as revealed by microarray analysis. Chromatin immunoprecipitation-real-time quantitative PCR showed that canonical p300-mediated acetylation of histones also facilitated transcription in response to TGF-ß1 stimulation. Interestingly, although both TGF-ß1-mediated and stiffness-mediated HSC activation require p300, comparison of gene expression data sets revealed that transcriptional targets of TGF-ß1 were distinct from those of stiffness-p300 mechanosignaling. Lastly, in tumor/HSC coinjection and intrasplenic tumor injection models, targeting p300 of activated-HSC/myofibroblasts by C646, short hairpin RNA, or cre-mediated gene disruption reduced tumor and liver metastatic growth in mice. Conclusion: p300 facilitates TGF-ß1-stimulated HSC activation by both noncanonical (cytoplasm-to-nucleus shuttle for SMAD2/3 and TAZ) and canonical (histone acetylation) mechanisms. p300 is an attractive target for inhibiting HSC activation and the prometastatic liver microenvironment.

Therapeutic targeting of BET bromodomain proteins in castration-resistant prostate cancer.

Men who develop metastatic castration-resistant prostate cancer (CRPC) invariably succumb to the disease. Progression to CRPC after androgen ablation therapy is predominantly driven by deregulated androgen receptor (AR) signalling. Despite the success of recently approved therapies targeting AR signalling, such as abiraterone and second-generation anti-androgens including MDV3100 (also known as enzalutamide), durable responses are limited, presumably owing to acquired resistance. Recently, JQ1 and I-BET762 two selective small-molecule inhibitors that target the amino-terminal bromodomains of BRD4, have been shown to exhibit anti-proliferative effects in a range of malignancies. Here we show that AR-signalling-competent human CRPC cell lines are preferentially sensitive to bromodomain and extraterminal (BET) inhibition. BRD4 physically interacts with the N-terminal domain of AR and can be disrupted by JQ1 (refs 11, 13). Like the direct AR antagonist MDV3100, JQ1 disrupted AR recruitment to target gene loci. By contrast with MDV3100, JQ1 functions downstream of AR, and more potently abrogated BRD4 localization to AR target loci and AR-mediated gene transcription, including induction of the TMPRSS2-ERG gene fusion and its oncogenic activity. In vivo, BET bromodomain inhibition was more efficacious than direct AR antagonism in CRPC xenograft mouse models. Taken together, these studies provide a novel epigenetic approach for the concerted blockade of oncogenic drivers in advanced prostate cancer.

Indel detection from DNA and RNA sequencing data with transIndel.

BACKGROUND: Insertions and deletions (indels) are a major class of genomic variation associated with human disease. Indels are primarily detected from DNA sequencing (DNA-seq) data but their transcriptional consequences remain unexplored due to challenges in discriminating medium-sized and large indels from splicing events in RNA-seq data. RESULTS: Here, we developed transIndel, a splice-aware algorithm that parses the chimeric alignments predicted by a short read aligner and reconstructs the mid-sized insertions and large deletions based on the linear alignments of split reads from DNA-seq or RNA-seq data. TransIndel exhibits competitive or superior performance over eight state-of-the-art indel detection tools on benchmarks using both synthetic and real DNA-seq data. Additionally, we applied transIndel to DNA-seq and RNA-seq datasets from 333 primary prostate cancer patients from The Cancer Genome Atlas (TCGA) and 59 metastatic prostate cancer patients from AACR-PCF Stand-Up- To-Cancer (SU2C) studies. TransIndel enhanced the taxonomy of DNA- and RNA-level alterations in prostate cancer by identifying recurrent FOXA1 indels as well as exitron splicing in genes implicated in disease progression. CONCLUSIONS: Our study demonstrates that transIndel is a robust tool for elucidation of medium- and large-sized indels from DNA-seq and RNA-seq data. Including RNA-seq in indel discovery efforts leads to significant improvements in sensitivity for identification of med-sized and large indels missed by DNA-seq, and reveals non-canonical RNA-splicing events in genes associated with disease pathology.

Lineage-Specific Effector Signatures of Invariant NKT Cells Are Shared amongst γδ T, Innate Lymphoid, and Th Cells.

Invariant NKT cells differentiate into three predominant effector lineages in the steady state. To understand these lineages, we sorted undifferentiated invariant NK T progenitor cells and each effector population and analyzed their transcriptional profiles by RNAseq. Bioinformatic comparisons were made to effector subsets among other lymphocytes, specifically Th cells, innate lymphoid cells (ILC), and γδ T cells. Myc-associated signature genes were enriched in NKT progenitors, like in other hematopoietic progenitors. Only NKT1 cells, but not NKT2 and NKT17 cells, had transcriptome similarity to NK cells and were also similar to other IFN-γ-producing lineages such as Th1, ILC1, and intraepithelial γδ T cells. NKT2 and NKT17 cells were similar to their analogous subsets of γδ T cells and ILCs, but surprisingly, not to Th2 and Th17 cells. We identified a set of genes common to each effector lineage regardless of Ag receptor specificity, suggesting the use of conserved regulatory cores for effector function.

[A SAS marco program for batch processing of univariate Cox regression analysis for great database].

OBJECTIVE: To realize batch processing of univariate Cox regression analysis for great database by SAS marco program. METHODS: We wrote a SAS macro program, which can filter, integrate, and export P values to Excel by SAS9.2. The program was used for screening survival correlated RNA molecules of ovarian cancer. RESULTS: A SAS marco program could finish the batch processing of univariate Cox regression analysis, the selection and export of the results. CONCLUSION: The SAS macro program has potential applications in reducing the workload of statistical analysis and providing a basis for batch processing of univariate Cox regression analysis.

EgoNet: identification of human disease ego-network modules.

BACKGROUND: Mining novel biomarkers from gene expression profiles for accurate disease classification is challenging due to small sample size and high noise in gene expression measurements. Several studies have proposed integrated analyses of microarray data and protein-protein interaction (PPI) networks to find diagnostic subnetwork markers. However, the neighborhood relationship among network member genes has not been fully considered by those methods, leaving many potential gene markers unidentified. The main idea of this study is to take full advantage of the biological observation that genes associated with the same or similar diseases commonly reside in the same neighborhood of molecular networks. RESULTS: We present EgoNet, a novel method based on egocentric network-analysis techniques, to exhaustively search and prioritize disease subnetworks and gene markers from a large-scale biological network. When applied to a triple-negative breast cancer (TNBC) microarray dataset, the top selected modules contain both known gene markers in TNBC and novel candidates, such as RAD51 and DOK1, which play a central role in their respective ego-networks by connecting many differentially expressed genes. CONCLUSIONS: Our results suggest that EgoNet, which is based on the ego network concept, allows the identification of novel biomarkers and provides a deeper understanding of their roles in complex diseases.

PxBLAT: An efficient python binding library for BLAT.

We introduce PxBLAT, a Python library designed to enhance usability and efficiency in interacting with the BLAST-like alignment tool (BLAT). PxBLAT provides an intuitive Application Programming Interface (API) design, allowing the incorporation of its functionality directly into Python-based bioinformatics workflows. Moreover, PxBLAT's design philosophy emphasizes ease of use, memory efficiency, and the elimination of intermediary files and unnecessary system calls, thereby enhancing computational speed and user experience. Benchmark tests reveal its superior performance across various datasets, illustrating its capacity to maintain correctness. PxBLAT supports Python (version 3.9+), and pre-compiled packages are released via PyPI (https://pypi.org/project/pxblat/) and Bioconda (https://anaconda.org/bioconda/pxblat). The source code and executable are freely available for academic, nonprofit, and personal use. Its documentation is available on ReadTheDocs (https://pxblat.readthedocs.io/en/latest/).

Expression and Therapeutic Targeting of TROP-2 in Treatment-Resistant Prostate Cancer.

PURPOSE: Men with metastatic castration-resistant prostate cancer (mCRPC) frequently develop resistance to androgen receptor signaling inhibitor (ARSI) treatment; therefore, new therapies are needed. Trophoblastic cell-surface antigen (TROP-2) is a transmembrane protein identified in prostate cancer and overexpressed in multiple malignancies. TROP-2 is a therapeutic target for antibody-drug conjugates (ADC). EXPERIMENTAL DESIGN: TROP-2 gene (TACSTD2) expression and markers of treatment resistance from prostate biopsies were analyzed using data from four previously curated cohorts of mCRPC (n = 634) and the PROMOTE study (dbGaP accession phs001141.v1.p1, n = 88). EPCAM or TROP-2-positive circulating tumor cells (CTC) were captured from peripheral blood for comparison of protein (n = 15) and gene expression signatures of treatment resistance (n = 40). We assessed the efficacy of TROP-2-targeting agents in a mouse xenograft model generated from prostate cancer cell lines. RESULTS: We demonstrated that TACSTD2 is expressed in mCRPC from luminal and basal tumors but at lower levels in patients with neuroendocrine prostate cancer. Patients previously treated with ARSI showed no significant difference in TACSTD2 expression, whereas patients with detectable AR-V7 expression showed increased expression. We observed that TROP-2 can serve as a cell surface target for isolating CTCs, which may serve as a predictive biomarker for ADCs. We also demonstrated that prostate cancer cell line xenografts can be targeted specifically by labeled anti-TROP-2 agents in vivo. CONCLUSIONS: These results support further studies on TROP-2 as a therapeutic and diagnostic target for mCRPC.