BCAR4 Expression as a Predictive Biomarker for Endocrine Therapy Resistance in Breast Cancer.

BACKGROUND: Breast cancer, particularly the estrogen receptor positive (ER+) subtype, remains a leading cause of cancer-related death among women. Endocrine therapy is the most effective treatment for ER+ breast cancer; however, the development of resistance presents a significant challenge. This study explored the role of the breast cancer antiestrogen resistance 4 (BCAR4) gene as a potential driver of resistance and a pivotal biomarker in breast cancer. PATIENTS AND METHODS: The researchers undertook a comprehensive analysis of 1743 patients spanning 6 independent cohorts. They examined the association of BCAR4 expression with patient outcomes across all breast cancer types and the PAM50 molecular subtypes. The relationship between elevated BCAR4 expression and resistance to endocrine therapy including AIs, the prevailing standard-of-care for endocrine therapy, was also investigated. RESULTS: This meta-analysis corroborated the link between BCAR4 expression and adverse outcomes as well as resistance to endocrine therapy in breast cancer. Notably, BCAR4 expression is clinically significant in luminal A and B subtypes. Additionally, an association between BCAR4 expression and resistance to AI treatment was discerned. CONCLUSION: This study expands on previous findings by demonstrating that BCAR4 expression is associated with resistance to newer therapies. The identification of patients with intrinsic resistance to hormone therapy is crucial to avoid ineffective treatment strategies. These findings contribute to our understanding of endocrine therapy resistance in breast cancer and could potentially guide the development of more effective treatment strategies.

Single cell-transcriptomic analysis informs the lncRNA landscape in metastatic castration resistant prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) is a lethal form of prostate cancer. Although long-noncoding RNAs (lncRNAs) have been implicated in mCRPC, past studies have relied on bulk sequencing methods with low depth and lack of single-cell resolution. Hence, we performed a lncRNA-focused analysis of single-cell RNA-sequencing data (n = 14) from mCRPC biopsies followed by integration with bulk multi-omic datasets. This yielded 389 cell-enriched lncRNAs in prostate cancer cells and the tumor microenvironment (TME). These lncRNAs demonstrated enrichment with regulatory elements and exhibited alterations during prostate cancer progression. Prostate-lncRNAs were correlated with AR mutational status and response to treatment with enzalutamide, while TME-lncRNAs were associated with RB1 deletions and poor prognosis. Finally, lncRNAs identified between prostate adenocarcinomas and neuroendocrine tumors exhibited distinct expression and methylation profiles. Our findings demonstrate the ability of single-cell analysis to refine our understanding of lncRNAs in mCRPC and serve as a resource for future mechanistic studies.

Genomic and epigenomic analysis of plasma cell-free DNA identifies stemness features associated with worse survival in AR -altered lethal prostate cancer.

Metastatic castration-resistant prostate cancer (mCRPC) resistant to androgen receptor (AR)-targeted agents is often lethal. Unfortunately, biomarkers for this deadly disease remain under investigation, and underpinning mechanisms are ill-understood. Here, we applied deep sequencing to ∼100 mCRPC patients prior to the initiation of first-line AR-targeted therapy, which detected AR /enhancer alterations in over a third of patients, which correlated with lethality. To delve into the mechanism underlying why these patients with cell-free AR /enhancer alterations developed more lethal prostate cancer, we next performed genome-wide cell-free DNA epigenomics. Strikingly, we found that binding sites for transcription factors associated with developmental stemness were nucleosomally more accessible. These results were corroborated using cell-free DNA methylation data, as well as tumor RNA sequencing from a held-out cohort of mCRPC patients. Thus, we validated the importance of AR /enhancer alterations as a prognostic biomarker in lethal mCRPC, and showed that the underlying mechanism for lethality involves reprogramming developmental states toward increased stemness.

Single-cell transcriptomics reveals long noncoding RNAs associated with tumor biology and the microenvironment in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) is highly heterogeneous and lethal. Long noncoding RNAs (lncRNAs) are an important class of genes regulating tumorigenesis and progression. Prior bulk transcriptomic studies in PDAC have revealed the dysregulation of lncRNAs but lack single-cell resolution to distinguish lncRNAs in tumor-intrinsic biology and the tumor microenvironment (TME). We analyzed single-cell transcriptome data from 73 multiregion samples in 21 PDAC patients to evaluate lncRNAs associated with intratumoral heterogeneity and the TME in PDAC. We found 111 cell-specific lncRNAs that reflected tumor, immune and stromal cell contributions, associated with outcomes, and validated across orthogonal datasets. Single-cell analysis of tumor cells revealed lncRNAs associated with TP53 mutations and FOLFIRINOX treatment that were obscured in bulk tumor analysis. Lastly, tumor subcluster analysis revealed widespread intratumor heterogeneity and intratumoral lncRNAs associated with cancer hallmarks and tumor processes such as angiogenesis, epithelial-mesenchymal transition, metabolism and immune signaling. Intratumoral subclusters and lncRNAs were validated across six datasets and showed clinically relevant associations with patient outcomes. Our study provides the first comprehensive assessment of the lncRNA landscape in PDAC using single-cell transcriptomic data and can serve as a resource, PDACLncDB (accessible at https://www.maherlab.com/pdaclncdb-overview), to guide future functional studies.

PACT: a pipeline for analysis of circulating tumor DNA.

MOTIVATION: Detection of genomic alterations in circulating tumor DNA (ctDNA) is currently used for active clinical monitoring of cancer progression and treatment response. While methods for analysis of small mutations are more developed, strategies for detecting structural variants (SVs) in ctDNA are limited. Additionally, reproducibly calling small-scale mutations, copy number alterations, and SVs in ctDNA is challenging due to the lack to unified tools for these different classes of variants. RESULTS: We developed a unified pipeline for the analysis of ctDNA [Pipeline for the Analysis of ctDNA (PACT)] that accurately detects SVs and consistently outperformed similar tools when applied to simulated, cell line, and clinical data. We provide PACT in the form of a Common Workflow Language pipeline which can be run by popular workflow management systems in high-performance computing environments. AVAILABILITY AND IMPLEMENTATION: PACT is freely available at https://github.com/ChrisMaherLab/PACT.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival.

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

CrypticProteinDB: an integrated database of proteome and immunopeptidome derived non-canonical cancer proteins.

Translated non-canonical proteins derived from noncoding regions or alternative open reading frames (ORFs) can contribute to critical and diverse cellular processes. In the context of cancer, they also represent an under-appreciated source of targets for cancer immunotherapy through their tumor-enriched expression or by harboring somatic mutations that produce neoantigens. Here, we introduce the largest integration and proteogenomic analysis of novel peptides to assess the prevalence of non-canonical ORFs (ncORFs) in more than 900 patient proteomes and 26 immunopeptidome datasets across 14 cancer types. The integrative proteogenomic analysis of whole-cell proteomes and immunopeptidomes revealed peptide support for a nonredundant set of 9760 upstream, downstream, and out-of-frame ncORFs in protein coding genes and 12811 in noncoding RNAs. Notably, 6486 ncORFs were derived from differentially expressed genes and 340 were ubiquitously translated across eight or more cancers. The analysis also led to the discovery of thirty-four epitopes and eight neoantigens from non-canonical proteins in two cohorts as novel cancer immunotargets. Collectively, our analysis integrated both bottom-up proteogenomic and targeted peptide validation to illustrate the prevalence of translated non-canonical proteins in cancer and to provide a resource for the prioritization of novel proteins supported by proteomic, immunopeptidomic, genomic and transcriptomic data, available at https://www.maherlab.com/crypticproteindb.

Large, Nested Variant of Urothelial Carcinoma Is Enriched with Activating Mutations in Fibroblast Growth Factor Receptor-3 among Other Targetable Mutations.

The large, nested variant of urothelial carcinoma (LNVUC) is characterized by bland histomorphology mimicking that of benign von Brunn nests. In the current study, we aimed to investigate the Fibroblast Growth Factor Receptor-3 (FGFR-3) activation and missense mutation in 38 cases, including 6 cases diagnosed with LNVUC and 32 with metastatic invasive urothelial carcinoma (UC). Initially, six formalin-fixed paraffin-embedded (FFPE) tissue samples of the LNVUC were subjected to whole-exome sequencing (WES), and then we performed targeted sequencing on 32 cases of metastatic invasive UC of various morphological subtypes, which were interrogated for the FGFR3. Our results revealed 3/6 (50%) LNVUC cases evaluated by WES in our study showed an activating mutation in FGFR-3, 33% showed an activating mutation in PIK3CA, and 17% showed activating mutation in GNAS or MRE11. Additionally, 33% of cases showed a truncating mutation in CDKN1B. All LNVUC in our study that harbored the FGFR-3 mutation showed additional activating or truncating mutations in other genes. Overall, 6/32 (18.75%) cases of random metastatic invasive UC showed missense mutations of the FGFR-3 gene. The LNVUC variant showed the higher incidence of FGFR-3 mutations compared to other types of mutations. Additionally, all LNVUC cases show additional activating or truncating mutations in other genes, thus being amenable to novel targeted therapy.

Characterization of cell-type specific circular RNAs associated with colorectal cancer metastasis.

Colorectal cancer (CRC) is the most common gastrointestinal malignancy and a leading cause of cancer deaths in the United States. More than half of CRC patients develop metastatic disease (mCRC) with an average 5-year survival rate of 13%. Circular RNAs (circRNAs) have recently emerged as important tumorigenesis regulators; however, their role in mCRC progression remains poorly characterized. Further, little is known about their cell-type specificity to elucidate their functions in the tumor microenvironment (TME). To address this, we performed total RNA sequencing (RNA-seq) on 30 matched normal, primary and metastatic samples from 14 mCRC patients. Additionally, five CRC cell lines were sequenced to construct a circRNA catalog in CRC. We detected 47 869 circRNAs, with 51% previously unannotated in CRC and 14% novel candidates when compared to existing circRNA databases. We identified 362 circRNAs differentially expressed in primary and/or metastatic tissues, termed circular RNAs associated with metastasis (CRAMS). We performed cell-type deconvolution using published single-cell RNA-seq datasets and applied a non-negative least squares statistical model to estimate cell-type specific circRNA expression. This predicted 667 circRNAs as exclusively expressed in a single cell type. Collectively, this serves as a valuable resource, TMECircDB (accessible at https://www.maherlab.com/tmecircdb-overview), for functional characterization of circRNAs in mCRC, specifically in the TME.

Integrated analysis of genomic and transcriptomic data for the discovery of splice-associated variants in cancer.

Somatic mutations within non-coding regions and even exons may have unidentified regulatory consequences that are often overlooked in analysis workflows. Here we present RegTools ( www.regtools.org ), a computationally efficient, free, and open-source software package designed to integrate somatic variants from genomic data with splice junctions from bulk or single cell transcriptomic data to identify variants that may cause aberrant splicing. We apply RegTools to over 9000 tumor samples with both tumor DNA and RNA sequence data. RegTools discovers 235,778 events where a splice-associated variant significantly increases the splicing of a particular junction, across 158,200 unique variants and 131,212 unique junctions. To characterize these somatic variants and their associated splice isoforms, we annotate them with the Variant Effect Predictor, SpliceAI, and Genotype-Tissue Expression junction counts and compare our results to other tools that integrate genomic and transcriptomic data. While many events are corroborated by the aforementioned tools, the flexibility of RegTools also allows us to identify splice-associated variants in known cancer drivers, such as TP53, CDKN2A, and B2M, and other genes.

Pan-Cancer Analysis Reveals Recurrent BCAR4 Gene Fusions across Solid Tumors.

Chromosomal rearrangements often result in active regulatory regions juxtaposed upstream of an oncogene to generate an expressed gene fusion. Repeated activation of a common downstream partner-with differing upstream regions across a patient cohort-suggests a conserved oncogenic role. Analysis of 9,638 patients across 32 solid tumor types revealed an annotated long noncoding RNA (lncRNA), Breast Cancer Anti-Estrogen Resistance 4 (BCAR4), was the most prevalent, uncharacterized, downstream gene fusion partner occurring in 11 cancers. Its oncogenic role was confirmed using multiple cell lines with endogenous BCAR4 gene fusions. Furthermore, overexpressing clinically prevalent BCAR4 gene fusions in untransformed cell lines was sufficient to induce an oncogenic phenotype. We show that the minimum common region to all gene fusions harbors an open reading frame that is necessary to drive proliferation. IMPLICATIONS: BCAR4 gene fusions represent an underappreciated class of gene fusions that may have biological and clinical implications across solid tumors.

LINC00355 regulates p27KIP expression by binding to MENIN to induce proliferation in late-stage relapse breast cancer.

Late-stage relapse (LSR) in patients with breast cancer (BC) occurs more than five years and up to 10 years after initial treatment and has less than 30% 5-year relative survival rate. Long non-coding RNAs (lncRNAs) play important roles in BC yet have not been studied in LSR BC. Here, we identify 1127 lncRNAs differentially expressed in LSR BC via transcriptome sequencing and analysis of 72 early-stage and 24 LSR BC patient tumors. Decreasing expression of the most up-regulated lncRNA, LINC00355, in BC and MCF7 long-term estrogen deprived cell lines decreases cellular invasion and proliferation. Subsequent mechanistic studies show that LINC00355 binds to MENIN and changes occupancy at the CDKN1B promoter to decrease p27Kip. In summary, this is a key study discovering lncRNAs in LSR BC and LINC00355 association with epigenetic regulation and proliferation in BC.

DANSR: A Tool for the Detection of Annotated and Novel Small RNAs.

Existing small noncoding RNA analysis tools are optimized for processing short sequencing reads (17-35 nucleotides) to monitor microRNA expression. However, these strategies under-represent many biologically relevant classes of small noncoding RNAs in the 36-200 nucleotides length range (tRNAs, snoRNAs, etc.). To address this, we developed DANSR, a tool for the detection of annotated and novel small RNAs using sequencing reads with variable lengths (ranging from 17-200 nt). While DANSR is broadly applicable to any small RNA dataset, we applied it to a cohort of matched normal, primary, and distant metastatic colorectal cancer specimens to demonstrate its ability to quantify annotated small RNAs, discover novel genes, and calculate differential expression. DANSR is available as an open source tool.

Loss of Long Noncoding RNA NXTAR in Prostate Cancer Augments Androgen Receptor Expression and Enzalutamide Resistance.

Androgen receptor (AR) signaling continues to play a dominant role in all stages of prostate cancer, including castration-resistant prostate cancers (CRPC) that have developed resistance to second generation AR antagonists such as enzalutamide. In this study, we identified a long noncoding RNA (lncRNA), NXTAR (LOC105373241) that is located convergent with the AR gene and is repressed in human prostate tumors and cell lines. NXTAR bound upstream of the AR promoter and promoted EZH2 recruitment, causing significant loss of AR (and AR-V7) expression. Paradoxically, AR bound the NXTAR promoter, and inhibition of AR by the ACK1/TNK2 small molecule inhibitor (R)-9b excluded AR from the NXTAR promoter. The histone acetyltransferase GCN5 bound and deposited H3K14 acetylation marks, enhancing NXTAR expression. Application of an oligonucleotide derived from NXTAR exon 5 (NXTAR-N5) suppressed AR/AR-V7 expression and prostate cancer cell proliferation, indicating the translational relevance of the negative regulation of AR. In addition, pharmacologic restoration of NXTAR using (R)-9b abrogated enzalutamide-resistant prostate xenograft tumor growth. Overall, this study uncovers a positive feedback loop, wherein NXTAR acts as a novel prostate tumor-suppressing lncRNA by inhibiting AR/AR-V7 expression, which in turn upregulates NXTAR levels, compromising enzalutamide-resistant prostate cancer. The restoration of NXTAR could serve as a new therapeutic modality for patients who have acquired resistance to second generation AR antagonists. SIGNIFICANCE: This study identifies NXTAR as a tumor suppressive lncRNA that can epigenetically downregulate AR/AR-V7 expression and provides a therapeutic strategy to reinstate NXTAR expression for treating recurrent CRPC.

ctDNA MRD Detection and Personalized Oncogenomic Analysis in Oligometastatic Colorectal Cancer From Plasma and Urine.

We hypothesized that circulating tumor DNA (ctDNA) molecular residual disease (MRD) analysis without prior mutational knowledge could be performed after neoadjuvant chemotherapy to assess oligometastatic colorectal cancer (CRC) treated surgically with curative intent. We also investigated urine as an alternative analyte for ctDNA MRD detection in this nongenitourinary setting. PATIENTS AND METHODS: We applied AVENIO targeted next-generation sequencing to plasma, tumor, and urine samples acquired on the day of curative-intent surgery from 24 prospectively enrolled patients with oligometastatic CRC. Age-related clonal hematopoiesis was accounted for by removing variants also present in white blood cells. Plasma and urine ctDNA MRD were correlated with tumor cells detected in the surgical specimen, and adjuvant treatment strategies were proposed based on ctDNA-inferred tumor mutational burden (iTMB) and targetable alterations. RESULTS: Seventy-one percent of patients were treated with neoadjuvant chemotherapy. Tumor-naive plasma ctDNA analysis detected MRD at a median level of 0.62% with 95% sensitivity and 100% specificity, and 94% and 77% sensitivity when only considering patients treated with neoadjuvant chemotherapy and putative driver mutations, respectively. In urine, ctDNA MRD detection specificity remained high at 100%, but sensitivity decreased to 64% with median levels being 11-fold lower than in plasma (P < .0001). Personalized ctDNA MRD oncogenomic analysis revealed 81% of patients might have been candidates for adjuvant immunotherapy based on high iTMB or targeted therapy based on actionable PIK3CA mutations. CONCLUSION: Tumor-naive plasma ctDNA analysis can sensitively and specifically detect MRD in patients with oligometastatic CRC after neoadjuvant chemotherapy. Urine-based ctDNA MRD detection is also feasible; however, it is less sensitive than plasma because of significantly lower levels. Oligometastatic patients with detectable MRD may benefit from additional personalized treatment based on ctDNA-derived oncogenomic profiling.

Phase 1 study combining alisertib with nab-paclitaxel in patients with advanced solid malignancies.

AIM: Aurora kinase A (AURKA) is a pleiotropic serine/threonine kinase that orchestrates mitotic progression. Paclitaxel stabilises microtubules and disrupts mitotic spindle assembly. The combination of AURKA inhibitor (alisertib) plus paclitaxel may be synergistic in rapidly proliferative cancers. We evaluated the safety and maximum tolerated dose (MTD) of alisertib in combination with nab-paclitaxel and its preliminary efficacy in patients with refractory high-grade neuroendocrine tumours (NETs). METHOD: This is a two-part, Phase 1 study. In Part A (dose escalation), a standard 3 + 3 design was used to determine MTD. In Part B (dose expansion), patients with predominantly refractory high-grade NETs were enrolled. RESULTS: In total, 31 patients were enrolled and treated (16 in Part A and 15 in Part B). The MTD of alisertib was 40 mg BID on D1-3 per week and nab-paclitaxel 100mg/m2 weekly: 3 weeks, 1 week off. Dose-limiting toxicity was neutropenia, and other common side-effects included fatigue, mucositis, and diarrhoea. In Part A, a patient with small-cell lung cancer with partial response (PR) was treated for more than 2 years, whereas four other patients with pancreatic ductal adenocarcinoma (one patient), small cell lung cancer (SCLC) (two patients), or high-grade NET (one patient) achieved stable disease (SD). In Part B, 13 of 15 enrolled patients had high-grade NETs. Of these, one had PR, and four had SD for more than 10 months. CONCLUSIONS: The combination of alisertib and nab-paclitaxel has manageable side-effect profile and showed promising preliminary efficacy in high-grade NETs, warranting further testing. TRIAL REGISTRATION: ClinicalTrials.gov identifier: NCT01677559.

A community challenge to evaluate RNA-seq, fusion detection, and isoform quantification methods for cancer discovery.

The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from the inference of the impacts of somatic variants to pathway analysis to biomarker development and subtype discovery. The ICGC-TCGA DREAM Somatic Mutation Calling in RNA (SMC-RNA) challenge was a crowd-sourced effort to benchmark methods for RNA isoform quantification and fusion detection from bulk cancer RNA sequencing (RNA-seq) data. It concluded in 2018 with a comparison of 77 fusion detection entries and 65 isoform quantification entries on 51 synthetic tumors and 32 cell lines with spiked-in fusion constructs. We report the entries used to build this benchmark, the leaderboard results, and the experimental features associated with the accurate prediction of RNA species. This challenge required submissions to be in the form of containerized workflows, meaning each of the entries described is easily reusable through CWL and Docker containers at https://github.com/SMC-RNA-challenge. A record of this paper's transparent peer review process is included in the supplemental information.

Long noncoding RNAs in cancer metastasis.

Metastasis is a major contributor to cancer-associated deaths. It is characterized by a multistep process that occurs through the acquisition of molecular and phenotypic changes enabling cancer cells from a primary tumour to disseminate and colonize at distant organ sites. Over the past decade, the discovery and characterization of long noncoding RNAs (lncRNAs) have revealed the diversity of their regulatory roles, including key contributions throughout the metastatic cascade. Here, we review how lncRNAs promote metastasis by functioning in discrete pro-metastatic steps including the epithelial-mesenchymal transition, invasion and migration and organotrophic colonization, and by influencing the metastatic tumour microenvironment, often by interacting within ribonucleoprotein complexes or directly with other nucleic acid entities. We discuss well-characterized lncRNAs with in vivo phenotypes and highlight mechanistic commonalities such as convergence with the TGFß-ZEB1/ZEB2 axis or the nuclear factor-κB pathway, in addition to lncRNAs with controversial mechanisms and the influence of methodologies on mechanistic interpretation. Furthermore, some lncRNAs can help identify tumours with increased metastatic risk and spur novel therapeutic strategies, with several lncRNAs having shown potential as novel targets for antisense oligonucleotide therapy in animal models. In addition to well-characterized examples of lncRNAs functioning in metastasis, we discuss controversies and ongoing challenges in lncRNA biology. Finally, we present areas for future study for this rapidly evolving field.

Long, Noncoding RNA Dysregulation in Glioblastoma.

Transcription occurs across more than 70% of the human genome and more than half of currently annotated genes produce functional noncoding RNAs. Of these transcripts, the majority-long, noncoding RNAs (lncRNAs)-are greater than 200 nucleotides in length and are necessary for various roles in the cell. It is increasingly appreciated that these lncRNAs are relevant in both health and disease states, with the brain expressing the largest number of lncRNAs compared to other organs. Glioblastoma (GBM) is an aggressive, fatal brain tumor that demonstrates remarkable intratumoral heterogeneity, which has made the development of effective therapies challenging. The cooperation between genetic and epigenetic alterations drives rapid adaptation that allows therapeutic evasion and recurrence. Given the large repertoire of lncRNAs in normal brain tissue and the well-described roles of lncRNAs in molecular and cellular processes, these transcripts are important to consider in the context of GBM heterogeneity and treatment resistance. Herein, we review the general mechanisms and biological roles of lncRNAs, with a focus on GBM, as well as RNA-based therapeutics currently in development.

Targeted Therapy to ß3 Integrin Reduces Chemoresistance in Breast Cancer Bone Metastases.

Breast cancer bone metastases are common and incurable. Tumoral integrin ß3 (ß3) expression is induced through interaction with the bone microenvironment. Although ß3 is known to promote bone colonization, its functional role during therapy of established bone metastases is not known. We found increased numbers of ß3+ tumor cells in murine bone metastases after docetaxel chemotherapy. ß3+ tumor cells were present in 97% of post-neoadjuvant chemotherapy triple-negative breast cancer patient samples (n = 38). High tumoral ß3 expression was associated with worse outcomes in both pre- and postchemotherapy triple-negative breast cancer groups. Genetic deletion of tumoral ß3 had minimal effect in vitro, but significantly enhanced in vivo docetaxel activity, particularly in the bone. Rescue experiments confirmed that this effect required intact ß3 signaling. Ultrastructural, transcriptomic, and functional analyses revealed an alternative metabolic response to chemotherapy in ß3-expressing cells characterized by enhanced oxygen consumption, reactive oxygen species generation, and protein production. We identified mTORC1 as a candidate for therapeutic targeting of this ß3-mediated, chemotherapy-induced metabolic response. mTORC1 inhibition in combination with docetaxel synergistically attenuated murine bone metastases. Furthermore, micelle nanoparticle delivery of mTORC1 inhibitor to cells expressing activated αvß3 integrins enhanced docetaxel efficacy in bone metastases. Taken together, we show that ß3 integrin induction by the bone microenvironment promotes resistance to chemotherapy through an altered metabolic response that can be defused by combination with αvß3-targeted mTORC1 inhibitor nanotherapy. Our work demonstrates the importance of the metastatic microenvironment when designing treatments and presents new, bone-specific strategies for enhancing chemotherapeutic efficacy.