The Human Intermediate Prolactin Receptor I-tail Contributes Breast Oncogenesis by Targeting Ras/MAPK Pathway.

Prolactin and its receptor (PRLr) in humans are significantly involved in breast cancer pathogenesis. The intermediate form of human PRLr (hPRLrI) is produced by alternative splicing and has a novel 13 amino acid tail ("I-tail") gain. hPRLrI induces significant proliferation and anchorage-independent growth of normal mammary epithelia in vitro when coexpressed with the long form hPRLr (hPRLrL). hPRLrL and hPRLrI coexpression is necessary to induce the transformation of mammary epithelia in vivo. The I-tail is associated with the ubiquitin-like protein neural precursor cell expressed developmentally downregulated protein 8. Treatment with the neural precursor cell expressed developmentally downregulated protein 8-activating enzyme inhibitor pevonedistat resulted in increased hPRLrL and the death of breast cancer cells. The goal of this study was to determine the function of the hPRLrI I-tail in hPRLrL/hPRLrI-mediated mammary transformation. hPRLrL/hPRLrI and hPRLrL/hPRLrIΔ13 (I-tail removal mutant) were delivered to MCF10AT cells. Cell proliferation was decreased when hPRLrI I-tail was removed. I-tail deletion decreased anchorage-independent growth and attenuated cell migration. The I-tail was involved in Ras/MAPK signaling but not PI3K/Akt signaling pathway as shown by western blot. I-tail removal resulted in decreased hPRLrI stability. RNA-sequencing data revealed that I-tail removal resulted in differential gene expression induced by prolactin. Ingenuity Pathway Analysis revealed that the activity of ERK was attenuated. Treatment of breast cancer cells with ERK1/2 inhibitor ulixertinib resulted in decreased colony-forming ability and less proliferation. These studies suggest that the hPRLrI I-tail contributed to breast oncogenesis and may be a promising target for the development of new breast cancer therapies.

Assessment of Patient-Derived Xenograft Growth and Antitumor Activity: The NCI PDXNet Consensus Recommendations.

Although patient-derived xenografts (PDXs) are commonly used for preclinical modeling in cancer research, a standard approach to in vivo tumor growth analysis and assessment of antitumor activity is lacking, complicating comparison of different studies and determination of whether a PDX experiment has produced evidence needed to consider a new therapy promising. We present consensus recommendations for assessment of PDX growth and antitumor activity, providing public access to a suite of tools for in vivo growth analyses. We expect that harmonizing PDX study design and analysis and access to a suite of analytical tools will enhance information exchange and facilitate identification of promising novel therapies and biomarkers for guiding cancer therapy.

Machine and deep learning methods for predicting 3D genome organization.

Three-Dimensional (3D) chromatin interactions, such as enhancer-promoter interactions (EPIs), loops, Topologically Associating Domains (TADs), and A/B compartments play critical roles in a wide range of cellular processes by regulating gene expression. Recent development of chromatin conformation capture technologies has enabled genome-wide profiling of various 3D structures, even with single cells. However, current catalogs of 3D structures remain incomplete and unreliable due to differences in technology, tools, and low data resolution. Machine learning methods have emerged as an alternative to obtain missing 3D interactions and/or improve resolution. Such methods frequently use genome annotation data (ChIP-seq, DNAse-seq, etc.), DNA sequencing information (k-mers, Transcription Factor Binding Site (TFBS) motifs), and other genomic properties to learn the associations between genomic features and chromatin interactions. In this review, we discuss computational tools for predicting three types of 3D interactions (EPIs, chromatin interactions, TAD boundaries) and analyze their pros and cons. We also point out obstacles of computational prediction of 3D interactions and suggest future research directions.

Evaluation of the NRF1-proteasome axis as a therapeutic target in breast cancer.

Proteasomes are multi-subunit complexes that specialize in protein degradation. Cancer cells exhibit a heightened dependence on proteasome activity, presumably to support their enhanced proliferation and other cancer-related characteristics. Here, a systematic analysis of TCGA breast cancer datasets revealed that proteasome subunit transcript levels are elevated in all intrinsic subtypes (luminal, HER2-enriched, and basal-like/triple-negative) when compared to normal breast tissue. Although these observations suggest a pan-breast cancer utility for proteasome inhibitors, our further experiments with breast cancer cell lines and patient-derived xenografts (PDX) pointed to triple-negative breast cancer (TNBC) as the most sensitive subtype to proteasome inhibition. Finally, using TNBC cells, we extended our studies to in vivo xenograft experiments. Our previous work has firmly established a cytoprotective role for the transcription factor NRF1 via its ability to upregulate proteasome genes in response to proteasome inhibition. In further support of this notion, we show here that NRF1 depletion significantly reduced tumor burden in an MDA-MB-231 TNBC xenograft mouse model treated with carfilzomib. Taken together, our results point to TNBC as a particularly vulnerable breast cancer subtype to proteasome inhibition and provide a proof-of-principle for targeting NRF1 as a viable means to increase the efficacy of proteasome inhibitors in TNBC tumors.

Stratification of Tamoxifen Synergistic Combinations for the Treatment of ER+ Breast Cancer.

Breast cancer alone accounts for the majority of cancer deaths among women, with the most commonly diagnosed subtype being estrogen receptor positive (ER+). Survival has greatly improved for patients with ER+ breast cancer, due in part to the development of antiestrogen compounds, such as tamoxifen. While treatment of the primary disease is often successful, as many as 30% of patients will experience recurrence and metastasis, mainly due to developed endocrine therapy resistance. In this study, we discovered two tamoxifen combination therapies, with simeprevir and VX-680, that reduce the tumor burden in animal models of ER+ breast cancer more than either compound or tamoxifen alone. Additionally, these tamoxifen combinations reduced the expression of HER2, a hallmark of tamoxifen treatment, which can facilitate acquisition of a treatment-resistant phenotype. These combinations could provide clinical benefit by potentiating tamoxifen treatment in ER+ breast cancer.

excluderanges: exclusion sets for T2T-CHM13, GRCm39, and other genome assemblies.

SUMMARY: Exclusion regions are sections of reference genomes with abnormal pileups of short sequencing reads. Removing reads overlapping them improves biological signal, and these benefits are most pronounced in differential analysis settings. Several labs created exclusion region sets, available primarily through ENCODE and Github. However, the variety of exclusion sets creates uncertainty which sets to use. Furthermore, gap regions (e.g. centromeres, telomeres, short arms) create additional considerations in generating exclusion sets. We generated exclusion sets for the latest human T2T-CHM13 and mouse GRCm39 genomes and systematically assembled and annotated these and other sets in the excluderanges R/Bioconductor data package, also accessible via the BEDbase.org API. The package provides unified access to 82 GenomicRanges objects covering six organisms, multiple genome assemblies, and types of exclusion regions. For human hg38 genome assembly, we recommend hg38.Kundaje.GRCh38_unified_blacklist as the most well-curated and annotated, and sets generated by the Blacklist tool for other organisms. AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/excluderanges/. Package website: https://dozmorovlab.github.io/excluderanges/.

Rewiring of the 3D genome during acquisition of carboplatin resistance in a triple-negative breast cancer patient-derived xenograft.

Changes in the three-dimensional (3D) structure of the genome are an emerging hallmark of cancer. Cancer-associated copy number variants and single nucleotide polymorphisms promote rewiring of chromatin loops, disruption of topologically associating domains (TADs), active/inactive chromatin state switching, leading to oncogene expression and silencing of tumor suppressors. However, little is known about 3D changes during cancer progression to a chemotherapy-resistant state. We integrated chromatin conformation capture (Hi-C), RNA-seq, and whole-genome sequencing obtained from triple-negative breast cancer patient-derived xenograft primary tumors (UCD52) and carboplatin-resistant samples and found increased short-range (< 2 Mb) interactions, chromatin looping, formation of TAD, chromatin state switching into a more active state, and amplification of ATP-binding cassette transporters. Transcriptome changes suggested the role of long-noncoding RNAs in carboplatin resistance. Rewiring of the 3D genome was associated with TP53, TP63, BATF, FOS-JUN family of transcription factors and led to activation of aggressiveness-, metastasis- and other cancer-related pathways. Integrative analysis highlighted increased ribosome biogenesis and oxidative phosphorylation, suggesting the role of mitochondrial energy metabolism. Our results suggest that 3D genome remodeling may be a key mechanism underlying carboplatin resistance.

Discovering Synergistic Compounds with BYL-719 in PI3K Overactivated Basal-like PDXs.

Basal-like triple-negative breast cancer (TNBC) tumor cells are difficult to eliminate due to resistance mechanisms that promote survival. While this breast cancer subtype has low PIK3CA mutation rates when compared to estrogen receptor-positive (ER+) breast cancers, most basal-like TNBCs have an overactive PI3K pathway due to gene amplification or high gene expression. BYL-719 is a PIK3CA inhibitor that has been found to have low drug-drug interactions, which increases the likelihood that it could be useful for combinatorial therapy. Alpelisib (BYL-719) with fulvestrant was recently approved for treating ER+ breast cancer patients whose cancer had developed resistance to ER-targeting therapy. In these studies, a set of basal-like patient-derived xenograft (PDX) models was transcriptionally defined with bulk and single-cell RNA-sequencing and clinically actionable mutation profiles defined with Oncomine mutational profiling. This information was overlaid onto therapeutic drug screening results. BYL-719-based, synergistic two-drug combinations were identified with 20 different compounds, including everolimus, afatinib, and dronedarone, which were also found to be effective at minimizing tumor growth. These data support the use of these drug combinations towards cancers with activating PIK3CA mutations/gene amplifications or PTEN deficient/PI3K overactive pathways.

Transcriptomic changes underlying EGFR inhibitor resistance in human and mouse models of basal-like breast cancer.

The goals of this study were to identify transcriptomic changes that arise in basal-like breast cancer cells during the development of resistance to epidermal growth factor receptor inhibitors (EGFRi) and to identify drugs that are cytotoxic once EGFRi resistance occurs. Human patient-derived xenografts (PDXs) were grown in immunodeficient mice and treated with a set of EGFRi; the EGFRi erlotinib was selected for more expansive in vivo studies. Single-cell RNA sequencing was performed on mammary tumors from the basal-like PDX WHIM2 that was treated with vehicle or erlotinib for 9 weeks. The PDX was then subjected to long-term erlotinib treatment in vivo. Through serial passaging, an erlotinib-resistant subline of WHIM2 was generated. Bulk RNA-sequencing was performed on parental and erlotinib-resistant tumors. In vitro high-throughput drug screening with > 500 clinically used compounds was performed on parental and erlotinib-resistant cells. Previously published bulk gene expression microarray data from MMTV-Wnt1 tumors were contrasted with the WHIM2 PDX data. Erlotinib effectively inhibited WHIM2 tumor growth for approximately 4 weeks. Compared to untreated cells, single-cell RNA sequencing revealed that a greater proportion of erlotinib-treated cells were in the G1 phase of the cell cycle. Comparison of WHIM2 and MMTV-Wnt1 gene expression data revealed a set of 38 overlapping genes that were differentially expressed in the erlotinib-resistant WHIM2 and MMTV-Wnt1 tumors. Comparison of all three data types revealed five genes that were upregulated across all erlotinib-resistant samples: IL19, KLK7, LCN2, SAA1, and SAA2. Of these five genes, LCN2 was most abundantly expressed in triple-negative breast cancers, and its knockdown restored erlotinib sensitivity in vitro. Despite transcriptomic differences, parental and erlotinib-resistant WHIM2 displayed similar responses to the majority of drugs assessed for cytotoxicity in vitro. This study identified transcriptomic changes arising in erlotinib-resistant basal-like breast cancer. These data could be used to identify a biomarker or develop a gene signature predictive of patient response to EGFRi. Future studies should explore the predictive capacity of these gene signatures as well as how LCN2 contributes to the development of EGFRi resistance.

Single-Molecule Sensor for High-Confidence Detection of miRNA.

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.

Exploitation of Sulfated Glycosaminoglycan Status for Precision Medicine of Triplatin in Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer lacking targetable biomarkers. TNBC is known to be most aggressive and when metastatic is often drug-resistant and uncurable. Biomarkers predicting response to therapy improve treatment decisions and allow personalized approaches for patients with TNBC. This study explores sulfated glycosaminoglycan (sGAG) levels as a predictor of TNBC response to platinum therapy. sGAG levels were quantified in three distinct TNBC tumor models, including cell line-derived, patient-derived xenograft (PDX) tumors, and isogenic models deficient in sGAG biosynthesis. The in vivo antitumor efficacy of Triplatin, a sGAG-directed platinum agent, was compared in these models with the clinical platinum agent, carboplatin. We determined that >40% of TNBC PDX tissue microarray samples have high levels of sGAGs. The in vivo accumulation of Triplatin in tumors as well as antitumor efficacy of Triplatin positively correlated with sGAG levels on tumor cells, whereas carboplatin followed the opposite trend. In carboplatin-resistant tumor models expressing high levels of sGAGs, Triplatin decreased primary tumor growth, reduced lung metastases, and inhibited metastatic growth in lungs, liver, and ovaries. sGAG levels served as a predictor of Triplatin sensitivity in TNBC. Triplatin may be particularly beneficial in treating patients with chemotherapy-resistant tumors who have evidence of residual disease after standard neoadjuvant chemotherapy. More effective neoadjuvant and adjuvant treatment will likely improve clinical outcome of TNBC.

Genomic screening reveals ubiquitin-like modifier activating enzyme 1 as a potent and druggable target in c-MYC-high triple negative breast cancer models.

Triple negative breast cancer (TNBC) accounts for over 30% of all breast cancer (BC)-related deaths, despite accounting for only 10% to 15% of total BC cases. Targeted therapy development has largely stalled in TNBC, underlined by a lack of traditionally druggable addictions like receptor tyrosine kinases (RTKs). Here, through full genome CRISPR/Cas9 screening of TNBC models, we have uncovered the sensitivity of TNBCs to the depletion of the ubiquitin-like modifier activating enzyme 1 (UBA1). Targeting UBA1 with the first-in-class UBA1 inhibitor TAK-243 induced unresolvable endoplasmic reticulum (ER)-stress and activating transcription factor 4 (ATF4)-mediated upregulation of proapoptotic NOXA, leading to cell death. c-MYC expression correlates with TAK-243 sensitivity and cooperates with TAK-243 to induce a stress response and cell death. Importantly, there was an order of magnitude greater sensitivity of TNBC lines to TAK-243 compared to normal tissue-derived cells. In five patient derived xenograft models (PDXs) of TNBC, TAK-243 therapy led to tumor inhibition or frank tumor regression. Moreover, in an intracardiac metastatic model of TNBC, TAK-243 markedly reduced metastatic burden, indicating UBA1 is a potential new target in TNBC expressing high levels of c-MYC.

Identification of nuclear export inhibitor-based combination therapies in preclinical models of triple-negative breast cancer.

An estimated 284,000 Americans will be diagnosed with breast cancer in 2021. Of these individuals, 15-20% have basal-like triple-negative breast cancer (TNBC), which is known to be highly metastatic. Chemotherapy is standard of care for TNBC patients, but chemoresistance is a common clinical problem. There is currently a lack of alternative, targeted treatment strategies for TNBC; this study sought to identify novel therapeutic combinations to treat basal-like TNBCs. For these studies, four human basal-like TNBC cell lines were utilized to determine the cytotoxicity profile of 1363 clinically-used drugs. Ten promising therapeutic candidates were identified, and synergism studies were performed in vitro. Two drug combinations that included KPT-330, an XPO1 inhibitor, were synergistic in all four cell lines. In vivo testing of four basal-like patient-derived xenografts (PDX) identified one combination, KPT-330 and GSK2126458 (a PI3K/mTOR inhibitor), that decreased tumor burden in mice significantly more than monotherapy with either single agent. Bulk and single-cell RNA-sequencing, immunohistochemistry, and analysis of published genomic datasets found that XPO1 was abundantly expressed in human basal-like TNBC cell lines, PDXs, and patient tumor samples. Within basal-like PDXs, XPO1 overexpression was associated with increased proliferation at the cellular level. Within patient datasets, XPO1 overexpression was correlated with greater rates of metastasis in patients with basal-like tumors. These studies identify a promising potential new combination therapy for patients with basal-like breast cancer.

Serine residues 726 and 780 have nonredundant roles regulating STAT5a activity in luminal breast cancer.

In breast cancer, prolactin-induced activation of the transcription factor STAT5a results from the phosphorylation of STAT5a tyrosine residue 694. However, its role in mammary oncogenesis remains an unsettled debate as STAT5a exhibits functional dichotomy with both pro-differentiative and pro-proliferative target genes. Phosphorylation of STAT5a serine residues, S726 and S780, may regulate STAT5a in such a way to underlie this duality. Given hematopoiesis studies showing phospho-serine STAT5a as necessary for transformation, we hypothesized that serine phosphorylation regulates STAT5a activity to contribute to its role in mammary oncogenesis, specifically in luminal breast cancer. Here, phosphorylation of S726-, S780-, and Y694-STAT5a in response to prolactin in MCF7 luminal breast cancer cells was investigated with STAT5a knockdown and rescue with Y694F-, S726A-, or S780A-STAT5a, where the phospho-sites were mutated. RNA-sequencing and subsequent Ingenuity Pathway Analysis predicted that loss of each phospho-site differentially affected both prolactin-induced gene expression as well as functional pathways of breast cancer (e.g. cell survival, proliferation, and colony formation). In vitro studies of anchorage-independent growth and proliferation confirmed distinct phenotypes: whereas S780A-STAT5a decreased clonogenicity, S726A-STAT5a decreased proliferation in response to prolactin compared to wild type STAT5a. Collectively, these studies provide novel insights into STAT5a activation in breast cancer pathogenesis.

Chromatin conformation capture (Hi-C) sequencing of patient-derived xenografts: analysis guidelines.

BACKGROUND: Sequencing of patient-derived xenograft (PDX) mouse models allows investigation of the molecular mechanisms of human tumor samples engrafted in a mouse host. Thus, both human and mouse genetic material is sequenced. Several methods have been developed to remove mouse sequencing reads from RNA-seq or exome sequencing PDX data and improve the downstream signal. However, for more recent chromatin conformation capture technologies (Hi-C), the effect of mouse reads remains undefined. RESULTS: We evaluated the effect of mouse read removal on the quality of Hi-C data using in silico created PDX Hi-C data with 10% and 30% mouse reads. Additionally, we generated 2 experimental PDX Hi-C datasets using different library preparation strategies. We evaluated 3 alignment strategies (Direct, Xenome, Combined) and 3 pipelines (Juicer, HiC-Pro, HiCExplorer) on Hi-C data quality. CONCLUSIONS: Removal of mouse reads had little-to-no effect on data quality as compared with the results obtained with the Direct alignment strategy. Juicer extracted more valid chromatin interactions for Hi-C matrices, regardless of the mouse read removal strategy. However, the pipeline effect was minimal, while the library preparation strategy had the largest effect on all quality metrics. Together, our study presents comprehensive guidelines on PDX Hi-C data processing.

The human intermediate prolactin receptor is a mammary proto-oncogene.

The hormone prolactin (PRL) and its receptor (hPRLr) are significantly involved in breast cancer pathogenesis. The intermediate hPRLr (hPRLrI) is an alternatively-spliced isoform, capable of stimulating cellular viability and proliferation. An analogous truncated mouse PRLr (mPRLr) was recently found to be oncogenic when co-expressed with wild-type mPRLr. The goal of this study was to determine if a similar transforming event occurs with the hPRLr in human breast epithelial cells and to better understand the mechanism behind such transformation. hPRLrL+I co-expression in MCF10AT cells resulted in robust in vivo and in vitro transformation, while hPRLrI knock-down in MCF7 cells significantly decreased in vitro malignant potential. hPRLrL+I heterodimers displayed greater stability than hPRLrL homodimers, and while being capable of activating Jak2, Ras, and MAPK, they were unable to induce Stat5a tyrosine phosphorylation. Both immunohistochemical breast cancer tissue microarray data and RNA sequencing analyses using The Cancer Genome Atlas (TCGA) identified that higher hPRLrI expression associates with triple-negative breast cancer. These studies indicate the hPRLrI, when expressed alongside hPRLrL, participates in mammary transformation, and represents a novel oncogenic mechanism.

Breast cancer liver metastasis: current and future treatment approaches.

Nearly all fatalities arising from breast tumors are attributable to distant metastases. Breast cancer liver metastasis (BCLM) is associated with poor prognoses, with the median survival time being 2 to 3 years. Tumor intrinsic subtype directs preferential metastasis to specific organs, with HER2-enriched tumors demonstrating the highest rates of metastasis to the liver, though all subtypes can grow in the liver. There is no singular established standard-of-care for BCLM; therapeutic selection is driven by histologic and molecular hallmarks of the primary tumor or biopsied metastasis samples. Given the poor prognosis of patients with hepatic spread, pre-clinical studies are necessary to identify and evaluate promising new treatment strategies. It is critical that these laboratory studies accurately recapitulate the BCLM disease process, standard progression, and histological attributes. In this review, we summarize the histologic and molecular characteristics of BCLM, evaluate the efficacy of existing surgical and medical treatment strategies, and discuss future approaches to preclinical study of BCLM.

Prolactin Drives a Dynamic STAT5A/HDAC6/HMGN2 Cis-Regulatory Landscape Exploitable in ER+ Breast Cancer.

The hormone prolactin has been implicated in breast cancer pathogenesis and regulates chromatin engagement by the transcription factor, STAT5A. STAT5A is known to inducibly bind promoters and cis-regulatory elements genome-wide, though the mechanisms by which it exerts specificity and regulation of target gene expression remain enigmatic. We previously identified HDAC6 and HMGN2 as cofactors that facilitate prolactin-induced, STAT5A-mediated gene expression. Here, multicondition STAT5A, HDAC6, and HMGN2 chromatin immunoprecipitation and sequencing with parallel condition RNA-seq are utilized to reveal the cis-regulatory landscape and cofactor dynamics underlying prolactin-stimulated gene expression in breast cancer. We find that prolactin-regulated genes are significantly enriched for cis-regulatory elements bound by HDAC6 and HMGN2, and that inducible STAT5A binding at enhancers, rather than promoters, conveys specificity for prolactin-regulated genes. The selective HDAC6 inhibitor, ACY-241, blocks prolactin-induced STAT5A chromatin engagement at cis-regulatory elements as well as a significant proportion of prolactin-stimulated gene expression. We identify functional pathways known to contribute to the development and/or progression of breast cancer that are activated by prolactin and inhibited by ACY-241. Additionally, we find that the DNA sequences underlying shared STAT5A and HDAC6 binding sites at enhancers are differentially enriched for estrogen response elements (ESR1 and ESR2 motifs) relative to enhancers bound by STAT5A alone. Gene set enrichment analysis identifies significant overlap of ERα-regulated genes with genes regulated by prolactin, particularly prolactin-regulated genes with promoters or enhancers co-occupied by both STAT5A and HDAC6. Lastly, the therapeutic efficacy of ACY-241 is demonstrated in in vitro and in vivo breast cancer models, where we identify synergistic ACY-241 drug combinations and observe differential sensitivity of ER+ models relative to ER- models.

Unexpected PD-L1 immune evasion mechanism in TNBC, ovarian, and other solid tumors by DR5 agonist antibodies.

Lack of effective immune infiltration represents a significant barrier to immunotherapy in solid tumors. Thus, solid tumor-enriched death receptor-5 (DR5) activating antibodies, which generates tumor debulking by extrinsic apoptotic cytotoxicity, remains a crucial alternate therapeutic strategy. Over past few decades, many DR5 antibodies moved to clinical trials after successfully controlling tumors in immunodeficient tumor xenografts. However, DR5 antibodies failed to significantly improve survival in phase-II trials, leading in efforts to generate second generation of DR5 agonists to supersize apoptotic cytotoxicity in tumors. Here we have discovered that clinical DR5 antibodies activate an unexpected immunosuppressive PD-L1 stabilization pathway, which potentially had contributed to their limited success in clinics. The DR5 agonist stimulated caspase-8 signaling not only activates ROCK1 but also undermines proteasome function, both of which contributes to increased PD-L1 stability on tumor cell surface. Targeting DR5-ROCK1-PD-L1 axis markedly increases immune effector T-cell function, promotes tumor regression, and improves overall survival in animal models. These insights have identified a potential clinically viable combinatorial strategy to revive solid cancer immunotherapy using death receptor agonism.