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.

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/).

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.

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.

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.

Detecting Medium and Large Insertions and Deletions with transIndel.

Insertions and deletions (indels) are primarily detected from DNA sequencing (DNA-seq) data, but their transcriptional consequences remain unexplored due to challenges in distinguishing medium- and large-sized indels from RNA splicing events in RNA-seq data. We introduce 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. Here, we describe the method and provide a tutorial on the installation and application of transIndel.

Opposing transcriptional programs of KLF5 and AR emerge during therapy for advanced prostate cancer.

Endocrine therapies for prostate cancer inhibit the androgen receptor (AR) transcription factor. In most cases, AR activity resumes during therapy and drives progression to castration-resistant prostate cancer (CRPC). However, therapy can also promote lineage plasticity and select for AR-independent phenotypes that are uniformly lethal. Here, we demonstrate the stem cell transcription factor Krüppel-like factor 5 (KLF5) is low or absent in prostate cancers prior to endocrine therapy, but induced in a subset of CRPC, including CRPC displaying lineage plasticity. KLF5 and AR physically interact on chromatin and drive opposing transcriptional programs, with KLF5 promoting cellular migration, anchorage-independent growth, and basal epithelial cell phenotypes. We identify ERBB2 as a point of transcriptional convergence displaying activation by KLF5 and repression by AR. ERBB2 inhibitors preferentially block KLF5-driven oncogenic phenotypes. These findings implicate KLF5 as an oncogene that can be upregulated in CRPC to oppose AR activities and promote lineage plasticity.

Identification of mutations that cooperate with defects in B cell transcription factors to initiate leukemia.

The transcription factors PAX5, IKZF1, and EBF1 are frequently mutated in B cell acute lymphoblastic leukemia (B-ALL). We demonstrate that compound heterozygous loss of multiple genes critical for B and T cell development drives transformation, including Pax5+/-xEbf1+/-, Pax5+/-xIkzf1+/-, and Ebf1+/-xIkzf1+/- mice for B-ALL, or Tcf7+/-xIkzf1+/- mice for T-ALL. To identify genetic defects that cooperate with Pax5 and Ebf1 compound heterozygosity to initiate leukemia, we performed a Sleeping Beauty (SB) transposon screen that identified cooperating partners including gain-of-function mutations in Stat5b (~65%) and Jak1 (~68%), or loss-of-function mutations in Cblb (61%) and Myb (32%). These findings underscore the role of JAK/STAT5B signaling in B cell transformation and demonstrate roles for loss-of-function mutations in Cblb and Myb in transformation. RNA-Seq studies demonstrated upregulation of a PDK1>SGK3>MYC pathway; treatment of Pax5+/-xEbf1+/- leukemia cells with PDK1 inhibitors blocked proliferation in vitro. In addition, we identified a conserved transcriptional gene signature between human and murine leukemias characterized by upregulation of myeloid genes, most notably involving the GM-CSF pathway, that resemble a B cell/myeloid mixed-lineage leukemia. Thus, our findings identify multiple mechanisms that cooperate with defects in B cell transcription factors to generate either progenitor B cell or mixed B/myeloid-like leukemias.

Integrated protocol for exitron and exitron-derived neoantigen identification using human RNA-seq data with ScanExitron and ScanNeo.

Exitron splicing (EIS) events in cancers can disrupt functional protein domains to cause cancer driver effects. EIS has been recognized as a new source of tumor neoantigens. Here, we describe an integrated protocol for EIS and EIS-derived neoantigen identification using RNA-seq data. The protocol constitutes a step-by-step guide from data collection to neoantigen prediction. For complete details on the use and execution of this protocol, please refer to Wang et al. (2021).

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.

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 .

Heterogeneity Analysis of Esophageal Squamous Cell Carcinoma in Cell Lines, Tumor Tissues and Patient-Derived Xenografts.

Esophageal Squamous Cell Carcinoma (ESCC) is the predominant type of Esophageal Cancer (EC), accounting for nearly 88% of EC incidents worldwide. Importantly, it is also a life-threatening cancer for patients diagnosed in advanced stages, with only a 20% 5-year survival rate due to a limited number of actionable targets and therapeutic options. Increasing evidence has shown that inter-tumor and intra-tumor heterogeneity are widely distributed across ESCC tumor tissues. In our work, multi-omics data from ESCC cell lines, tumor tissue, normal tissue and Patient-Derived Xenograft (PDX) tissues were analyzed to investigate the heterogeneity among ESCC samples at the DNA, RNA, and protein level. We identified enrichment of ECM-receptor interaction and Focal adhesion pathways from the subset of protein-coding genes with non-silent mutations in ESCC patients. We also found that TP53, TTN, KMT2D, CSMD3, DNAH5, MUC16 and DST are the most frequently mutated genes in ESCC patient samples. Out of the identified genes, TP53 is the most frequently mutated, with 84 distinct non-silent mutation variants. We observed that p.R248Q, p.R175G/H, and p.R273C/H are the most common TP53 mutation variants. The diversity of TP53 mutations reveal its importance in ESCC progression and may also provide promising targets for precision therapeutics. Additionally, we identified the Olfactory transduction as the top signaling pathway, enriched from genes uniquely expressed in The Cancer Genome Atlas (TCGA)-ESCC patient tumor tissues, which may provide implications for the exact roles of the corresponding genes in ESCC. Cyclic nucleotide-gated channel subunit beta 1(CNGB1), a gene belonging to the Olfactory transduction pathway, was found exclusively overexpressed in ESCC. Expression of CNGB1 could serve as a marker, indicating potential diagnostic or therapeutic value. Finally, we investigated heterogeneity in the context of the ESCC PDX model, which is an emerging tool used to predict drug response and recapitulate tumor behavior in vivo. We observed trans-species heterogeneity in as high as 75% of the identified proteins, indicating that the ambiguity of proteins should be addressed by specific strategies to avoid drawing false conclusions. The identification and characterization of gene mutation and expression heterogeneity across different ESCC datasets, including various novel TP53 mutations, ECM-receptor interaction, Focal adhesion, and Olfactory transduction pathways (CNGB1), provide researchers with evidence and implications for accurate research and precision therapeutic development.

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.

SV-HotSpot: detection and visualization of hotspots targeted by structural variants associated with gene expression.

Whole genome sequencing (WGS) has enabled the discovery of genomic structural variants (SVs), including those targeting intergenic and intronic non-coding regions that eluded previous exome focused strategies. However, the field currently lacks an automated tool that analyzes SV candidates to identify recurrent SVs and their targeted sites (hotspot regions), visualizes these genomic events within the context of various functional elements, and evaluates their potential effect on gene expression. To address this, we developed SV-HotSpot, an automated tool that integrates SV candidates, copy number alterations, gene expression, and genome annotations (e.g. gene and regulatory elements) to discover, annotate, and visualize recurrent SVs and their targeted hotspot regions that may affect gene expression. We applied SV-HotSpot to WGS and matched transcriptome data from metastatic castration resistant prostate cancer patients and rediscovered recurrent SVs targeting coding and non-coding functional elements known to promote prostate cancer progression and metastasis. SV-HotSpot provides a valuable resource to integrate SVs, gene expression, and genome annotations for discovering biologically relevant SVs altering coding and non-coding genome. SV-HotSpot is available at https://github.com/ChrisMaherLab/SV-HotSpot .

ScanITD: Detecting internal tandem duplication with robust variant allele frequency estimation.

BACKGROUND: Internal tandem duplications (ITDs) are tandem duplications within coding exons and are important prognostic markers and drug targets for acute myeloid leukemia (AML). Next-generation sequencing has enabled the discovery of ITD at single-nucleotide resolution. ITD allele frequency is used in the risk stratification of patients with AML; higher ITD allele frequency is associated with poorer clinical outcomes. However, the ITD allele frequency data are often unavailable to treating physicians and the detection of ITDs with accurate variant allele frequency (VAF) estimation remains challenging for short-read sequencing. RESULTS: Here we present the ScanITD approach, which performs a stepwise seed-and-realignment procedure for ITD detection with accurate VAF prediction. The evaluations on simulated and real data demonstrate that ScanITD outperforms 3 state-of-the-art ITD detectors, especially for VAF estimation. Importantly, ScanITD yields better accuracy than general-purpose structural variation callers for predicting ITD size range duplications. CONCLUSIONS: ScanITD enables the accurate identification of ITDs with robust VAF estimation. ScanITD is written in Python and is open-source software that is freely accessible at https://github.com/ylab-hi/ScanITD.

The DNA methylation landscape of advanced prostate cancer.

Although DNA methylation is a key regulator of gene expression, the comprehensive methylation landscape of metastatic cancer has never been defined. Through whole-genome bisulfite sequencing paired with deep whole-genome and transcriptome sequencing of 100 castration-resistant prostate metastases, we discovered alterations affecting driver genes that were detectable only with integrated whole-genome approaches. Notably, we observed that 22% of tumors exhibited a novel epigenomic subtype associated with hypermethylation and somatic mutations in TET2, DNMT3B, IDH1 and BRAF. We also identified intergenic regions where methylation is associated with RNA expression of the oncogenic driver genes AR, MYC and ERG. Finally, we showed that differential methylation during progression preferentially occurs at somatic mutational hotspots and putative regulatory regions. This study is a large integrated study of whole-genome, whole-methylome and whole-transcriptome sequencing in metastatic cancer that provides a comprehensive overview of the important regulatory role of methylation in metastatic castration-resistant prostate cancer.

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.

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.

Targeting RET Kinase in Neuroendocrine Prostate Cancer.

The increased treatment of metastatic castration-resistant prostate cancer (mCRPC) with second-generation antiandrogen therapies (ADT) has coincided with a greater incidence of lethal, aggressive variant prostate cancer (AVPC) tumors that have lost dependence on androgen receptor (AR) signaling. These AR-independent tumors may also transdifferentiate to express neuroendocrine lineage markers and are termed neuroendocrine prostate cancer (NEPC). Recent evidence suggests kinase signaling may be an important driver of NEPC. To identify targetable kinases in NEPC, we performed global phosphoproteomics comparing several AR-independent to AR-dependent prostate cancer cell lines and identified multiple altered signaling pathways, including enrichment of RET kinase activity in the AR-independent cell lines. Clinical NEPC patient samples and NEPC patient-derived xenografts displayed upregulated RET transcript and RET pathway activity. Genetic knockdown or pharmacologic inhibition of RET kinase in multiple mouse and human models of NEPC dramatically reduced tumor growth and decreased cell viability. Our results suggest that targeting RET in NEPC tumors with high RET expression could be an effective treatment option. Currently, there are limited treatment options for patients with aggressive neuroendocrine prostate cancer and none are curative. IMPLICATIONS: Identification of aberrantly expressed RET kinase as a driver of tumor growth in multiple models of NEPC provides a significant rationale for testing the clinical application of RET inhibitors in patients with AVPC.

Focal Adhesion Kinase Promotes Hepatic Stellate Cell Activation by Regulating Plasma Membrane Localization of TGFß Receptor 2.

Transforming growth factor ß (TGFß) induces hepatic stellate cell (HSC) differentiation into tumor-promoting myofibroblast, although underlying mechanism remains incompletely understood. Focal adhesion kinase (FAK) is activated in response to TGFß stimulation, so it transmits TGFß stimulus to extracellular signal-regulated kinase and P38 mitogen-activated protein kinase signaling. However, it is unknown whether FAK can, in return, modulate TGFß receptors. In this study, we tested whether FAK phosphorylated TGFß receptor 2 (TGFßR2) and regulated TGFßR2 intracellular trafficking in HSCs. The FAKY397F mutant and PF-573,228 were used to inhibit the kinase activity of FAK, the TGFßR2 protein level was quantitated by immunoblotting, and HSC differentiation into myofibroblast was assessed by expression of HSC activation markers, alpha-smooth muscle actin, fibronectin, or connective tissue growth factor. We found that targeting FAK kinase activity suppressed the TGFßR2 protein level, TGFß1-induced mothers against decapentaplegic homolog phosphorylation, and myofibroblastic activation of HSCs. At the molecular and cellular level, active FAK (phosphorylated FAK at tyrosine 397) bound to TGFßR2 and kept TGFßR2 at the peripheral plasma membrane of HSCs, and it induced TGFßR2 phosphorylation at tyrosine 336. In contrast, targeting FAK or mutating Y336 to F on TGFßR2 led to lysosomal sorting and degradation of TGFßR2. Using RNA sequencing, we identified that the transcripts of 764 TGFß target genes were influenced by FAK inhibition, and that through FAK, TGFß1 stimulated HSCs to produce a panel of tumor-promoting factors, including extracellular matrix remodeling proteins, growth factors and cytokines, and immune checkpoint molecule PD-L1. Functionally, targeting FAK inhibited tumor-promoting effects of HSCs in vitro and in a tumor implantation mouse model. Conclusion: FAK targets TGFßR2 to the plasma membrane and protects TGFßR2 from lysosome-mediated degradation, thereby promoting TGFß-mediated HSC activation. FAK is a target for suppressing HSC activation and the hepatic tumor microenvironment.