Tumor Sequencing and Patient-Derived Xenografts in the Neoadjuvant Treatment of Breast Cancer

Pre-treatment peripheral blood immunophenotyping and response to neoadjuvant chemotherapy in operable breast cancer

BACKGROUND

Tumor immune infiltration and peripheral blood immune signatures have prognostic and predictive value in breast cancer. Whether distinct peripheral blood immune phenotypes are associated with response to neoadjuvant chemotherapy (NAC) remains understudied.

METHODS

Peripheral blood mononuclear cells from 126 breast cancer patients enrolled in a prospective clinical trial (NCT02022202) were analyzed using Cytometry by time-of-flight with a panel of 29 immune cell surface protein markers. Kruskal-Wallis tests or Wilcoxon rank-sum tests were used to evaluate differences in immune cell subpopulations according to breast cancer subtype and response to NAC.

RESULTS

There were 122 evaluable samples: 47 (38.5%) from patients with hormone receptor-positive, 39 (32%) triple-negative (TNBC), and 36 (29.5%) HER2-positive breast cancer. The relative abundances of pre-treatment peripheral blood T, B, myeloid, NK, and unclassified cells did not differ according to breast cancer subtype. In TNBC, higher pre-treatment myeloid cells were associated with lower pathologic complete response (pCR) rates. In hormone receptor-positive breast cancer, lower pre-treatment CD8 + naïve and CD4 + effector memory cells re-expressing CD45RA (TEMRA) T cells were associated with more extensive residual disease after NAC. In HER2 + breast cancer, the peripheral blood immune phenotype did not differ according to NAC response.

CONCLUSIONS

Pre-treatment peripheral blood immune cell populations (myeloid in TNBC; CD8 + naïve T cells and CD4 + TEMRA cells in luminal breast cancer) were associated with response to NAC in early-stage TNBC and hormone receptor-positive breast cancers, but not in HER2 + breast cancer.

TRIAL REGISTRATION

NCT02022202 . Registered 20 December 2013.

Prognostic predictive value of Ki-67 in stage I-II triple-negative breast cancer

Aim: Our research aimed to determine an optimal cutoff value and investigate the prognostic predictive function of Ki-67. Materials & methods: We retrospectively enrolled 1146 patients diagnosed with stage I-II triple-negative breast cancer. Disease-free and overall survival were analyzed using the Kaplan-Meier method and the Cox regression model. Results: We classified Ki-67 >45% as the high group (n = 716). A Ki-67 level of >45% was associated with poorer disease-free survival (p = 0.039) and overall survival (p = 0.029). Lymph node stage, neoadjuvant chemotherapy, and radiotherapy were independent predictive variables of prognosis. Conclusion: Triple-negative breast cancer may be further subcategorized according to the Ki-67 level. Neoadjuvant chemotherapy and postoperative radiotherapy can improve the prognosis of early triple-negative breast cancer.

Factors associated with engraftment success of patient-derived xenografts of breast cancer

BACKGROUND

Patient-derived xenograft (PDX) models serve as a valuable tool for the preclinical evaluation of novel therapies. They closely replicate the genetic, phenotypic, and histopathological characteristics of primary breast tumors. Despite their promise, the rate of successful PDX engraftment is various in the literature. This study aimed to identify the key factors associated with successful PDX engraftment of primary breast cancer.

METHODS

We integrated clinicopathological data with morphological attributes quantified using a trained artificial intelligence (AI) model to identify the principal factors affecting PDX engraftment.

RESULTS

Multivariate logistic regression analyses demonstrated that several factors, including a high Ki-67 labeling index (Ki-67LI) (p < 0.001), younger age at diagnosis (p = 0.032), post neoadjuvant chemotherapy (NAC) (p = 0.006), higher histologic grade (p = 0.039), larger tumor size (p = 0.029), and AI-assessed higher intratumoral necrosis (p = 0.027) and intratumoral invasive carcinoma (p = 0.040) proportions, were significant factors for successful PDX engraftment (area under the curve [AUC] 0.905). In the NAC group, a higher Ki-67LI (p < 0.001), lower Miller-Payne grade (p < 0.001), and reduced proportion of intratumoral normal breast glands as assessed by AI (p = 0.06) collectively provided excellent prediction accuracy for successful PDX engraftment (AUC 0.89).

CONCLUSIONS

We found that high Ki-67LI, younger age, post-NAC status, higher histologic grade, larger tumor size, and specific morphological attributes were significant factors for predicting successful PDX engraftment of primary breast cancer.

Identification of a Notch transcriptomic signature for breast cancer

BACKGROUND

Dysregulated Notch signalling contributes to breast cancer development and progression, but validated tools to measure the level of Notch signalling in breast cancer subtypes and in response to systemic therapy are largely lacking. A transcriptomic signature of Notch signalling would be warranted, for example to monitor the effects of future Notch-targeting therapies and to learn whether altered Notch signalling is an off-target effect of current breast cancer therapies. In this report, we have established such a classifier.

METHODS

To generate the signature, we first identified Notch-regulated genes from six basal-like breast cancer cell lines subjected to elevated or reduced Notch signalling by culturing on immobilized Notch ligand Jagged1 or blockade of Notch by γ-secretase inhibitors, respectively. From this cadre of Notch-regulated genes, we developed candidate transcriptomic signatures that were trained on a breast cancer patient dataset (the TCGA-BRCA cohort) and a broader breast cancer cell line cohort and sought to validate in independent datasets.

RESULTS

An optimal 20-gene transcriptomic signature was selected. We validated the signature on two independent patient datasets (METABRIC and Oslo2), and it showed an improved coherence score and tumour specificity compared with previously published signatures. Furthermore, the signature score was particularly high for basal-like breast cancer, indicating an enhanced level of Notch signalling in this subtype. The signature score was increased after neoadjuvant treatment in the PROMIX and BEAUTY patient cohorts, and a lower signature score generally correlated with better clinical outcome.

CONCLUSIONS

The 20-gene transcriptional signature will be a valuable tool to evaluate the response of future Notch-targeting therapies for breast cancer, to learn about potential effects on Notch signalling from conventional breast cancer therapies and to better stratify patients for therapy considerations.

The Mutational Spectrum of Pre- and Post-Neoadjuvant Chemotherapy Triple-Negative Breast Cancers

The response of triple-negative breast cancer (TNBC) patients to pre-operative (neoadjuvant chemotherapy) is a critical factor of their outcome. To determine the effects of chemotherapy on the tumor genome and to identify mutations associated with chemoresistance and sensitivity, we performed whole exome sequencing on pre/post-chemotherapy tumors and matched lymphocytes from 26 patients. We observed great inter-tumoral heterogeneity with no gene mutated recurrently in more than four tumors besides TP53. Although the degree of response to chemotherapy in residual tumors was associated with more subclonal changes during chemotherapy, there was minimal evolution between pre/post-tumors. Indeed, gene sets enriched for mutations in pre- and post-chemotherapy tumors were very similar and reflected genes involved in the biological process of neurogenesis. Somatically mutated genes present in chemosensitive tumors included COL1A2, PRMD15, APOBEC3B, PALB2 and histone protein encoding genes, while BRCA1, ATR, ARID1A, XRCC3 and genes encoding for tubulin-associated proteins were present in the chemoresistant tumors. We also found that the mutational spectrum of post-chemotherapy tumors was more reflective of matching metastatic tumor biopsies than pre-chemotherapy samples. These findings support a portrait of modest ongoing genomic instability with respect to single-nucleotide variants induced by or selected for by chemotherapy in TNBCs.

Patient Characteristics Associated with Growth of Patient-Derived Tumor Implants in Mice (Patient-Derived Xenografts)

Background: patient-derived xenografts (PDXs) have defined the field of translational cancer research in recent years, becoming one of the most-used tools in early drug development. The process of establishing cancer models in mice has turned out to be challenging, since little research focuses on evaluating which factors impact engraftment success. We sought to determine the clinical, pathological, or molecular factors which may predict better engraftment rates in PDXs. Methods: between March 2017 and January 2021, tumor samples obtained from patients with primary or metastatic cancer were implanted into athymic nude mice. A full comprehensive evaluation of baseline factors associated with the patients and patients' tumors was performed, with the goal of potentially identifying predictive markers of engraftment. We focused on clinical (patient factors) pathological (patients' tumor samples) and molecular (patients' tumor samples) characteristics, analyzed either by immunohistochemistry (IHC) or next-generation sequencing (NGS), which were associated with the likelihood of final engraftment, as well as with tumor growth rates in xenografts. Results: a total of 585 tumor samples were collected and implanted. Twenty-one failed to engraft, due to lack of malignant cells. Of 564 tumor-positive samples, 187 (33.2%) grew at time of analysis. The study was able to find correlation and predictive value for engraftment for the following: the use of systemic antibiotics by the patient within 2 weeks of sampling (38.1% (72/189) antibiotics- group vs. 30.7% (115/375) no-antibiotics) (p = 0.048), and the administration of systemic steroids to the patients within 2 weeks of sampling (41.5% (34/48) steroids vs. 31.7% (153/329), no-steroids) (p = 0.049). Regarding patient's baseline tests, we found certain markers could help predict final engraftment success: for lactate dehydrogenase (LDH) levels, 34.1% (140/411) of tumors derived from patients with baseline blood LDH levels above the upper limit of normality (ULN) achieved growth, against 30.7% (47/153) with normal LDH (p = 0.047). Histological tumor characteristics, such as grade of differentiation, were also correlated. Grade 1: 25.4% (47/187), grade 2: 34.8% (65/187) and grade 3: 40.1% (75/187) tumors achieved successful growth (p = 0.043), suggesting the higher the grade, the higher the likelihood of success. Similarly, higher ki67 levels were also correlated with better engraftment rates: low (Ki67 < 15%): 8.9% (9/45) achieved growth vs. high (Ki67 ≥ 15%): 31% (35/113) (p: 0.002). Other markers of aggressiveness such as the presence of lymphovascular invasion in tumor sample of origin was also predictive: 42.2% (97/230) with lymphovascular vs. 26.9% (90/334) of samples with no invasion (p = 0.0001). From the molecular standpoint, mismatch-repair-deficient (MMRd) tumors showed better engraftment rates: 62.1% (18/29) achieved growth vs. 40.8% (75/184) of proficient tumors (p = 0.026). A total of 84 PDX were breast models, among which 57.9% (11/19) ER-negative models grew, vs. 15.4% (10/65) of ER-positive models (p = 0.0001), also consonant with ER-negative tumors being more aggressive. BRAFmut cancers are more likely to achieve engraftment during the development of PDX models. Lastly, tumor growth rates during first passages can help establish a cutoff point for the decision-making process during PDX development, since the higher the tumor grades, the higher the likelihood of success. Conclusions: tumors with higher grade and Ki67 protein expression, lymphovascular and/or perineural invasion, with dMMR and are negative for ER expression have a higher probability of achieving growth in the process of PDX development. The use of steroids and/or antibiotics in the patient prior to sampling can also impact the likelihood of success in PDX development. Lastly, establishing a cutoff point for tumor growth rates could guide the decision-making process during PDX development.

Optical Diffraction Tomography and Raman Confocal Microscopy for the Investigation of Vacuoles Associated with Cancer Senescent Engulfing Cells

Wild-type p53 cancer therapy-induced senescent cells frequently engulf and degrade neighboring ones inside a massive vacuole in their cytoplasm. After clearance of the internalized cell, the vacuole persists, seemingly empty, for several hours. Despite large vacuoles being associated with cell death, this process is known to confer a survival advantage to cancer engulfing cells, leading to therapy resistance and tumor relapse. Previous attempts to resolve the vacuolar structure and visualize their content using dyes were unsatisfying for lack of known targets and ineffective dye penetration and/or retention. Here, we overcame this problem by applying optical diffraction tomography and Raman spectroscopy to MCF7 doxorubicin-induced engulfing cells. We demonstrated a real ability of cell tomography and Raman to phenotype complex microstructures, such as cell-in-cells and vacuoles, and detect chemical species in extremely low concentrations within live cells in a completely label-free fashion. We show that vacuoles had a density indistinguishable to the medium, but were not empty, instead contained diluted cell-derived macromolecules, and we could discern vacuoles from medium and cells using their Raman fingerprint. Our approach is useful for the noninvasive investigation of senescent engulfing (and other peculiar) cells in unperturbed conditions, crucial for a better understanding of complex biological processes.

Generation, evolution, interfering factors, applications, and challenges of patient-derived xenograft models in immunodeficient mice

Establishing appropriate preclinical models is essential for cancer research. Evidence suggests that cancer is a highly heterogeneous disease. This follows the growing use of cancer models in cancer research to avoid these differences between xenograft tumor models and patient tumors. In recent years, a patient-derived xenograft (PDX) tumor model has been actively generated and applied, which preserves both cell-cell interactions and the microenvironment of tumors by directly transplanting cancer tissue from tumors into immunodeficient mice. In addition to this, the advent of alternative hosts, such as zebrafish hosts, or in vitro models (organoids and microfluidics), has also facilitated the advancement of cancer research. However, they still have a long way to go before they become reliable models. The development of immunodeficient mice has enabled PDX to become more mature and radiate new vitality. As one of the most reliable and standard preclinical models, the PDX model in immunodeficient mice (PDX-IM) exerts important effects in drug screening, biomarker development, personalized medicine, co-clinical trials, and immunotherapy. Here, we focus on the development procedures and application of PDX-IM in detail, summarize the implications that the evolution of immunodeficient mice has brought to PDX-IM, and cover the key issues in developing PDX-IM in preclinical studies.

Integration of multiomics data shows down regulation of mismatch repair and tubulin pathways in triple-negative chemotherapy-resistant breast tumors

BACKGROUND

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). The response to NAC is prognostic, with reductions in overall survival and disease-free survival rates in those patients who do not achieve a pathological complete response (pCR). Based on this premise, we hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence.

METHODS AND RESULTS

We investigated 24 samples from 12 non-LAR TNBC patients with paired pre- and post-NAC data, including four patients with recurrence shortly after surgery (< 24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and nonrecurrent TNBC tumors; however, post-NAC samples demonstrated significant alterations in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the 9 paired non-LAR samples available in the NAC I-SPY1 trial confirmed 56 gene sets. Within these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n = 392) breast cancer dataset with relapse-free survival (RFS) data was used to refine our gene list to a 17-gene signature. A threefold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine-learning models. Due to the limited number of studies with pre- and post-NAC TNBC tumor data, further validation of the signature is needed.

CONCLUSION

Analysis of multiomics data from post-NAC TNBC chemoresistant tumors showed down regulation of mismatch repair and tubulin pathways. Additionally, we identified a 17-gene signature in TNBC associated with post-NAC recurrence enriched with down-regulated immune genes.

Patient-derived models: Promising tools for accelerating the clinical translation of breast cancer research findings

Breast cancer has become the highest incidence of cancer in women. It was extensively and deeply studied by biologists and medical workers worldwide. However, the meaningful results in lab researches cannot be realized in clinical, and a part of new drugs in clinical experiments do not obtain as good results as the preclinical researches. It is urgently that promote a kind of breast cancer research models that can get study results closer to the physiological condition of the human body. Patient-derived models (PDMs) originating from clinical tumor, contain primary elements of tumor and maintain key clinical features of tumor. So they are promising research models to facilitate laboratory researches translate to clinical application, and predict the treatment outcome of patients. In this review, we summarize the establishment of PDMs of breast cancer, reviewed the application of PDMs in clinical translational researches and personalized precision medicine with breast cancer as an example, to improve the understanding of PDMs among researchers and clinician, facilitate them to use PDMs on a large scale of breast cancer researches and promote the clinical translation of laboratory research and new drug development.

Pharmacological Targeting of Androgen Receptor Elicits Context-Specific Effects in Estrogen Receptor-Positive Breast Cancer

Androgen receptor (AR) is expressed in 80% to 90% of estrogen receptor α-positive (ER+) breast cancers. Accumulated evidence has shown that AR is a tumor suppressor and that its expression is associated with improved prognosis in ER+ breast cancer. However, both a selective AR agonist (RAD140) and an AR inhibitor (enzalutamide, ENZ) have shown a therapeutic effect on ER+ breast cancer, so the potential for clinical application of AR-targeting therapy for ER+ breast cancer is still in dispute. In this study, we evaluated the efficacy of ENZ and RAD140 in vivo and in vitro in AR+/ER+ breast cancer models, characterizing the relationship of AR and ER levels to response to AR-targeting drugs and investigating the alterations of global gene expression and chromatin binding of AR and ERα after ENZ treatment. In the AR-low setting, ENZ directly functioned as an ERα antagonist. Cell growth inhibition by ENZ in breast cancer with low AR expression was independent of AR and instead dependent on ER. In AR-high breast cancer models, AR repressed ERα signaling and ENZ promoted ERα signaling by antagonizing AR. In contrast, RAD140 activated AR signaling and suppressed AR-high tumor growth by deregulating ERα expression and blocking ERα function. Overall, analysis of the dynamic efficacies and outcomes of AR agonist, and antagonist in the presence of different AR and ERα levels reveals regulators of response and supports the clinical investigation of ENZ in selected ER+ tumors with a low AR/ER ratio and AR agonists in tumors with a high AR/ER ratio.

SIGNIFICANCE

The ratio of androgen receptor to estrogen receptor in breast cancer dictates the response to AR-targeted therapies, providing guidelines for developing AR-directed treatment strategies for patients with breast cancer.

Breast cancer patient-derived whole-tumor cell culture model for efficient drug profiling and treatment response prediction

Breast cancer (BC) is a complex disease comprising multiple distinct subtypes with different genetic features and pathological characteristics. Although a large number of antineoplastic compounds have been approved for clinical use, patient-to-patient variability in drug response is frequently observed, highlighting the need for efficient treatment prediction for individualized therapy. Several patient-derived models have been established lately for the prediction of drug response. However, each of these models has its limitations that impede their clinical application. Here, we report that the whole-tumor cell culture (WTC) ex vivo model could be stably established from all breast tumors with a high success rate (98 out of 116), and it could reassemble the parental tumors with the endogenous microenvironment. We observed strong clinical associations and predictive values from the investigation of a broad range of BC therapies with WTCs derived from a patient cohort. The accuracy was further supported by the correlation between WTC-based test results and patients' clinical responses in a separate validation study, where the neoadjuvant treatment regimens of 15 BC patients were mimicked. Collectively, the WTC model allows us to accomplish personalized drug testing within 10 d, even for small-sized tumors, highlighting its potential for individualized BC therapy. Furthermore, coupled with genomic and transcriptomic analyses, WTC-based testing can also help to stratify specific patient groups for assignment into appropriate clinical trials, as well as validate potential biomarkers during drug development.

Identification of Src Family Kinases as Potential Therapeutic Targets for Chemotherapy-Resistant Triple Negative Breast Cancer

Neoadjuvant chemotherapy (NAC) remains the cornerstone of the treatment for triple negative breast cancer (TNBC), with the goal of complete eradication of disease. However, for patients with residual disease after NAC, recurrence and mortality rates are high and the identification of novel therapeutic targets is urgently needed. We quantified tyrosine phosphorylation (pTyr)-mediated signaling networks in chemotherapy sensitive (CS) and resistant (CR) TNBC patient-derived xenografts (PDX), to gain novel therapeutic insights. The antitumor activity of SFK inhibition was examined in vivo. Treated tumors were further subjected to phosphoproteomic and RNAseq analysis, to identify the mechanism of actions of the drug. We identified Src Family Kinases (SFKs) as potential therapeutic targets in CR TNBC PDXs. Treatment with dasatinib, an FDA approved SFK inhibitor, led to inhibition of tumor growth in vivo. Further analysis of post-treatment PDXs revealed multiple mechanisms of actions of the drug, confirming the multi-target inhibition of dasatinib. Analysis of pTyr in tumor specimens suggested a low prevalence of SFK-driven tumors, which may provide insight into prior clinical trial results demonstrating a lack of dasatinib antitumor activity in unselected breast cancer patients. Taken together, these results underscore the importance of pTyr characterization of tumors, in identifying new targets, as well as stratifying patients based on their activated signaling networks for therapeutic options. Our data provide a strong rationale for studying SFK inhibitors in biomarker-selected SFK-driven TNBC.

A Molecularly Characterized Preclinical Platform of Subcutaneous Renal Cell Carcinoma (RCC) Patient-Derived Xenograft Models to Evaluate Novel Treatment Strategies

Renal cell carcinoma (RCC) is a kidney cancer with an onset mainly during the sixth or seventh decade of the patient’s life. Patients with advanced, metastasized RCC have a poor prognosis. The majority of patients develop treatment resistance towards Standard of Care (SoC) drugs within months. Tyrosine kinase inhibitors (TKIs) are the backbone of first-line therapy and have been partnered with an immune checkpoint inhibitor (ICI) recently. Despite the most recent progress, the development of novel therapies targeting acquired TKI resistance mechanisms in advanced and metastatic RCC remains a high medical need. Preclinical models with high translational relevance can significantly support the development of novel personalized therapies. It has been demonstrated that patient-derived xenograft (PDX) models represent an essential tool for the preclinical evaluation of novel targeted therapies and their combinations. In the present project, we established and molecularly characterized a comprehensive panel of subcutaneous RCC PDX models with well-conserved molecular and pathological features over multiple passages. Drug screening towards four SoC drugs targeting the vascular endothelial growth factor (VEGF) and PI3K/mTOR pathway revealed individual and heterogeneous response profiles in those models, very similar to observations in patients. As unique features, our cohort includes PDX models from metastatic disease and multi-tumor regions from one patient, allowing extended studies on intra-tumor heterogeneity (ITH). The PDX models are further used as basis for developing corresponding in vitro cell culture models enabling advanced high-throughput drug screening in a personalized context. PDX models were subjected to next-generation sequencing (NGS). Characterization of cancer-relevant features including driver mutations or cellular processes was performed using mutational and gene expression data in order to identify potential biomarker or treatment targets in RCC. In summary, we report a newly established and molecularly characterized panel of RCC PDX models with high relevance for translational preclinical research.

Luminal androgen receptor breast cancer subtype and investigation of the microenvironment and neoadjuvant chemotherapy response

Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype with low overall survival rates and high molecular heterogeneity; therefore, few targeted therapies are available. The luminal androgen receptor (LAR) is the most consistently identified TNBC subtype, but the clinical utility has yet to be established. Here, we constructed a novel genomic classifier, LAR-Sig, that distinguishes the LAR subtype from other TNBC subtypes and provide evidence that it is a clinically distinct disease. A meta-analysis of seven TNBC datasets (n = 1086 samples) from neoadjuvant clinical trials demonstrated that LAR patients have significantly reduced response (pCR) rates than non-LAR TNBC patients (odds ratio = 2.11, 95% CI: 1.33, 2.89). Moreover, deconvolution of the tumor microenvironment confirmed an enrichment of luminal epithelium corresponding with a decrease in basal and myoepithelium in LAR TNBC tumors. Increased immunosuppression in LAR patients may lead to a decreased presence of cycling T-cells and plasma cells. While, an increased presence of myofibroblast-like cancer-associated cells may impede drug delivery and treatment. In summary, the lower levels of tumor infiltrating lymphocytes (TILs), reduced immune activity in the micro-environment, and lower pCR rates after NAC, suggest that new therapeutic strategies for the LAR TNBC subtype need to be developed.

FOXA1 overexpression suppresses interferon signaling and immune response in cancer

Androgen receptor-positive prostate cancer (PCa) and estrogen receptor-positive luminal breast cancer (BCa) are generally less responsive to immunotherapy compared with certain tumor types such as melanoma. However, the underlying mechanisms are not fully elucidated. In this study, we found that FOXA1 overexpression inversely correlated with interferon (IFN) signature and antigen presentation gene expression in PCa and BCa patients. FOXA1 bound the STAT2 DNA-binding domain and suppressed STAT2 DNA-binding activity, IFN signaling gene expression, and cancer immune response independently of the transactivation activity of FOXA1 and its mutations detected in PCa and BCa. Increased FOXA1 expression promoted cancer immuno- and chemotherapy resistance in mice and PCa and BCa patients. These findings were also validated in bladder cancer expressing high levels of FOXA1. FOXA1 overexpression could be a prognostic factor to predict therapy resistance and a viable target to sensitize luminal PCa, BCa, and bladder cancer to immuno- and chemotherapy.

Establishment and characterization of immortalized human breast cancer cell lines from breast cancer patient-derived xenografts (PDX)

The application of patient-derived xenografts (PDX) in drug screening and testing is a costly and time-consuming endeavor. While cell lines permit extensive mechanistic studies, many human breast cancer cell lines lack patient characteristics and clinical treatment information. Establishing cell lines that retain patient's genetic and drug response information would enable greater drug screening and mechanistic studies. Therefore, we utilized breast cancer PDX from the Mayo Breast Cancer Genome Guided Therapy Study (BEAUTY) to establish two immortalized, genomically unique breast cancer cell lines. Through extensive genetic and therapeutic testing, the cell lines were found to retain the same clinical subtype, major somatic alterations, and drug response phenotypes as their corresponding PDX and patient tumor. Our findings demonstrate PDX can be utilized to develop immortalized breast cancer cell lines and provide a valuable tool for understanding the molecular mechanism of drug resistance and exploring novel treatment strategies.

Inhibition of ATM Induces Hypersensitivity to Proton Irradiation by Upregulating Toxic End Joining

Proton Bragg peak irradiation has a higher ionizing density than conventional photon irradiation or the entrance of the proton beam profile. Whether targeting the DNA damage response (DDR) could enhance vulnerability to the distinct pattern of damage induced by proton Bragg peak irradiation is currently unknown. Here, we performed genetic or pharmacologic manipulation of key DDR elements and evaluated DNA damage signaling, DNA repair, and tumor control in cell lines and xenografts treated with the same physical dose across a radiotherapy linear energy transfer spectrum. Radiotherapy consisted of 6 MV photons and the entrance beam or Bragg peak of a 76.8 MeV spot scanning proton beam. More complex DNA double-strand breaks (DSB) induced by Bragg peak proton irradiation preferentially underwent resection and engaged homologous recombination (HR) machinery. Unexpectedly, the ataxia-telangiectasia mutated (ATM) inhibitor, AZD0156, but not an inhibitor of ATM and Rad3-related, rendered cells hypersensitive to more densely ionizing proton Bragg peak irradiation. ATM inhibition blocked resection and shunted more DSBs to processing by toxic ligation through nonhomologous end-joining, whereas loss of DNA ligation via XRCC4 or Lig4 knockdown rescued resection and abolished the enhanced Bragg peak cell killing. Proton Bragg peak monotherapy selectively sensitized cell lines and tumor xenografts with inherent HR defects, and the repair defect induced by ATM inhibitor coadministration showed enhanced efficacy in HR-proficient models. In summary, inherent defects in HR or administration of an ATM inhibitor in HR-proficient tumors selectively enhances the relative biological effectiveness of proton Bragg peak irradiation. SIGNIFICANCE: Coadministration of an ATM inhibitor rewires DNA repair machinery to render cancer cells uniquely hypersensitive to DNA damage induced by the proton Bragg peak, which is characterized by higher density ionization.See related commentary by Nickoloff, p. 3156.

Patient-Derived Xenograft Engraftment and Breast Cancer Outcomes in a Prospective Neoadjuvant Study (BEAUTY)

PURPOSE

Patient-derived xenografts (PDX) are a research tool for studying cancer biology and drug response phenotypes. While engraftment rates are higher for tumors with more aggressive characteristics, it is uncertain whether engraftment is prognostic for cancer recurrence.

PATIENTS AND METHODS

In a prospective study of patients with breast cancer treated with neoadjuvant chemotherapy (NAC) with taxane ± trastuzumab followed by anthracycline-based chemotherapy, we report the association between breast cancer events and PDX engraftment using tumors derived from treatment naïve (pre-NAC biopsies from 113 patients) and treatment resistant (post-NAC at surgery from 34 patients). Gray test was used to assess whether the cumulative incidence of a breast cancer event differs with respect to either pre-NAC PDX engraftment or post-NAC PDX engraftment.

RESULTS

With a median follow-up of 5.7 years, the cumulative incidence of breast cancer relapse did not differ significantly according to pre-NAC PDX engraftment (5-year rate: 13.6% vs. 13.4%; P = 0.89). However, the incidence of a breast event was greater for patients with post-NAC PDX engraftment (5-year rate: 50.0% vs. 19.6%), but this did not achieve significance (P = 0.11).

CONCLUSIONS

In treatment-naïve breast cancer receiving standard NAC, PDX engraftment was not prognostic for breast cancer recurrence. Further study is needed to establish whether PDX engraftment in the treatment-resistant setting is prognostic for cancer recurrence.

Establishment of patient-derived xenograft models of adenoid cystic carcinoma to assess pre-clinical efficacy of combination therapy of a PI3K inhibitor and retinoic acid

Due to the difficulties and long periods of establishment, preclinical animal models of adenoid cystic carcinoma (ACC) are scarce but imperative. The researches involving molecular features and therapeutic targets of ACC require an integrated group of preclinical animal models which can credibly retain the heterogeneity of this tumor. Currently chemotherapies and targeting therapies have modest efficacy in ACC and the overall response rate is rather low. Therefore, novel therapeutic regimen of ACC is urgently needed and remains a major clinical challenge. We transplanted a group of tumor samples from human salivary ACC into immunodeficient mice to establish patient-derived xenografts (PDXs). Patient tumors and their matched PDXs were conducted histological analyses, whole-exome sequencing (WES) and RNA-seq respectively. 13 PDXs were successfully established from 34 ACC, involved in 3 histological types, including cribriform, tubular, and solid. These ACC PDXs generally reflected the histopathological and molecular features of their corresponding original tumors. MYB/MYBL1-NFIB fusion (53.85%) and high-frequency mutation genes, such as KDM6A, KMT2C, KMT2D, NOTCH1, NOTCH2, SMARCA4 and PIK3CA were mainly conserved in PDXs. Guided by the genetic alterations, the efficiencies of retinoic acid (RA) and a PI3K inhibitor were evaluated in ACC PDX models harboring both MYB fusion and PIK3CA amplification/mutation. Combination treatment of the PI3K inhibitor and RA demonstrated remarkable inhibition of tumors in PDXs harboring both PIK3CA mutation/amplification and MYB-NFIB fusion gene in vivo and in vitro. In this study, we displayed the morphologically and genetic featured PDXs which recapitulated the heterogeneity of original ACC tumors, indicating that the models could be used as a platform for drug screening for therapy response. The feasibility of combination treatment approaches for dual targets were confirmed, providing new regimens for personalized therapies in ACC.

Genomic profile of metastatic breast cancer patient-derived xenografts established using percutaneous biopsy

Background

Metastatic breast cancer (mBC) is a complex and life-threatening disease and although it is difficult to cure, patients can benefit from sequential anticancer treatment, including endocrine therapy, targeted therapy and cytotoxic chemotherapy. The patient-derived xenograft (PDX) model is suggested as a practical tool to predict the clinical outcome of this disease as well as to screen novel drugs. This study aimed to establish PDX models in Korean patients and analyze their genomic profiles and utility for translational research.

Methods

Percutaneous core needle biopsy or punch biopsy samples were used for xenotransplantation. Whole exome sequencing and transcriptome analysis were performed to assess the genomic and RNA expression profiles, respectively. Copy number variation and mutational burden were analyzed and compared with other metastatic breast cancer genomic results. Mutational signatures were also analyzed. The antitumor effect of an ATR inhibitor was tested in the relevant PDX model.

Results

Of the 151 cases studied, 40 (26%) PDX models were established. Notably, the take rate of all subtypes, including the hormone receptor-positive (HR +) subtype, exceeded 20%. The PDX model had genomic fidelity and copy number variation that represented the pattern of its donor sample. TP53, PIK3CA, ESR1, and GATA3 mutations were frequently found in our samples, with TP53 being the most frequently mutated, and the somatic mutations in these genes strengthened their frequency in the PDX model. The ESR1 mutation, CCND1 amplification, and the APOBEC signature were significant features in our HR + HER2- PDX model. Fulvestrant in combination with palbociclib showed a partial response to the relevant patient’s tumor harboring the ESR1 mutation, and CCND1 amplification was found in the PDX model. AZD6738, an ATR inhibitor, delayed tumor growth in a relevant PDX model.

Conclusions

Our PDX model was established using core needle biopsy samples from primary and metastatic tissues. Genomic profiles of the samples reflected their original tissue characteristics and could be used for the interpretation of clinical outcomes.

The Essential Factors of Establishing Patient-derived Tumor Model

Establishing an applicable preclinical model is vital for translational cancer research. Patient-derived xenograft has been important preclinical model systems and widely used for cancer research. Patient-derived xenograft models that represent the tumors of the patients are necessary to better translate research discoveries and to test potential therapeutic approaches. However, research in this field is hampered by the limited engraftment rate. In this review, we go over a large number of researches on patient-derived xenograft transplantation and firstly systematically summarize the main factors in methodology to successfully establish models. These results will be applied to the development of patient-derived xenograft leading to better preclinical research.

CDC25B partners with PP2A to induce AMPK activation and tumor suppression in triple negative breast cancer

Cell division cycle 25 (CDC25) dual specificity phosphatases positively regulate the cell cycle by activating cyclin-dependent kinase/cyclin complexes. Here, we demonstrate that in addition to its role in cell cycle regulation, CDC25B functions as a regulator of protein phosphatase 2A (PP2A), a major cellular Ser/Thr phosphatase, through its direct interaction with PP2A catalytic subunit. Importantly, CDC25B alters the regulation of AMP-activated protein kinase signaling (AMPK) by PP2A, increasing AMPK activity by inhibiting PP2A to dephosphorylate AMPK. CDC25B depletion leads to metformin resistance by inhibiting metformin-induced AMPK activation. Furthermore, dual inhibition of CDC25B and PP2A further inhibits growth of 3D organoids isolated from patient derived xenograft model of breast cancer compared to CDC25B inhibition alone. Our study identifies CDC25B as a regulator of PP2A, and uncovers a mechanism of controlling the activity of a key energy metabolism marker, AMPK.

iMOKA: k-mer based software to analyze large collections of sequencing data

iMOKA (interactive multi-objective k-mer analysis) is a software that enables comprehensive analysis of sequencing data from large cohorts to generate robust classification models or explore specific genetic elements associated with disease etiology. iMOKA uses a fast and accurate feature reduction step that combines a Naïve Bayes classifier augmented by an adaptive entropy filter and a graph-based filter to rapidly reduce the search space. By using a flexible file format and distributed indexing, iMOKA can easily integrate data from multiple experiments and also reduces disk space requirements and identifies changes in transcript levels and single nucleotide variants. iMOKA is available at https://github.com/RitchieLabIGH/iMOKA and Zenodo https://doi.org/10.5281/zenodo.4008947 .

XENOBREAST Trial: A prospective study of xenografts establishment from surgical specimens of patients with triple negative or luminal b breast cancer

Introduction: Patient-derived xenografts (PDX) can be used to explore tumour pathophysiology and could be useful to better understand therapeutic response in breast cancer. PDX from mammary tumours are usually made from metastatic tumours. Thus, PDX from primary mammary tumours or after neoadjuvant treatment are still rare. This study aims to assess the feasibility to establish xenografts from tumour samples of patients with triple negative or luminal B breast cancer in neoadjuvant, adjuvant or metastatic setting.

Methods: XENOBREAST is a single-centre and prospective study. This feasibility pilot trial aims to produce xenografts from tumour samples of patients with triple negative or luminal B breast cancer. Patient enrolment is expected to take 3 years: 85 patients will be enrolled and followed for 28 months. Additional blood samples will be taken as part of the study. Surgical specimens from post-NAC surgery, primary surgery or surgical excision of the metastases will be collected to establish PDX. Histomolecular characteristics of the established PDX will be investigated and compared with the initial histomolecular profile of the collected tumours to ensure that they are well-established.

Ethics and dissemination: XENOBREAST belongs to category 2 interventional research on the human person. This study has been approved by the Sud Méditerranée IV – Montpellier ethics committee. It is conducted notably in accordance with the Declaration of Helsinki and General Data Protection Regulation (GDPR). Study data and findings will be published in peer-reviewed medical journals. We also plan to present the study and all data at national congresses and conferences.

Registration: ClinicalTrials.gov ID NCT04133077; registered on October 21, 2019.

Pharmacogenomics of aromatase inhibitors in postmenopausal breast cancer and additional mechanisms of anastrozole action

Aromatase inhibitors (AIs) reduce breast cancer recurrence and prolong survival, but up to 30% of patients exhibit recurrence. Using a genome-wide association study of patients entered on MA.27, a phase III randomized trial of anastrozole versus exemestane, we identified a single nucleotide polymorphism (SNP) in CUB And Sushi multiple domains 1 (CSMD1) associated with breast cancer–free interval, with the variant allele associated with fewer distant recurrences. Mechanistically, CSMD1 regulates CYP19 expression in an SNP- and drug-dependent fashion, and this regulation is different among 3 AIs: anastrozole, exemestane, and letrozole. Overexpression of CSMD1 sensitized AI-resistant cells to anastrozole but not to the other 2 AIs. The SNP in CSMD1 that was associated with increased CSMD1 and CYP19 expression levels increased anastrozole sensitivity, but not letrozole or exemestane sensitivity. Anastrozole degrades estrogen receptor α (ERα), especially in the presence of estradiol (E2). ER⁺ breast cancer organoids and AI- or fulvestrant-resistant breast cancer cells were more sensitive to anastrozole plus E2 than to AI alone. Our findings suggest that the CSMD1 SNP might help to predict AI response, and anastrozole plus E2 serves as a potential new therapeutic strategy for patients with AI- or fulvestrant-resistant breast cancers.

A germline variation within the CSMD1 gene predicts aromatase inhibitor response in breast cancer.

Regulation of sister chromatid cohesion by nuclear PD-L1

Programmed death ligand-1 (PD-L1 or B7-H1) is well known for its role in immune checkpoint regulation, but its function inside the tumor cells has rarely been explored. Here we report that nuclear PD-L1 is important for cancer cell sister chromatid cohesion. We found that depletion of PD-L1 suppresses cancer cell proliferation, colony formation in vitro, and tumor growth in vivo in immune-deficient NSG mice independent of its role in immune checkpoint. Specifically, PD-L1 functions as a subunit of the cohesin complex, and its deficiency leads to formation of multinucleated cells and causes a defect in sister chromatid cohesion. Mechanistically, PD-L1 compensates for the loss of Sororin, whose expression is suppressed in cancer cells overexpressing PD-L1. PD-L1 competes with Wing Apart-Like (WAPL) for binding to PDS5B, and secures proper sister chromatid cohesion and segregation. Our findings suggest an important role for nuclear PD-L1 in cancer cells independent of its function in immune checkpoint.

Concordance between predicted HLA type using next generation sequencing data generated for non-HLA purposes and clinical HLA type

We explored the feasibility of obtaining accurate HLA type using pre-existing NGS data not generated for HLA purposes. 83 exomes and 500 targeted NGS pharmacogenomic panels were analyzed using Omixon HLA Explore, OptiType, and/or HLA-Genotyper software. Results were compared against clinical HLA genotyping. 765 (94.2%) Omixon and 769 (94.7%) HLA-Genotyper of 812 germline allele calls across class I/II loci and 402 (99.5%) of 404 OptiType class I calls were concordant to the second field (i.e. HLA-A*02:01). An additional 19 (2.3%) Omixon, 39 (4.8%) HLA-Genotyper, and 2 (0.5%) OptiType allele calls were first field concordant (i.e. HLA-A*02). Using Omixon, four alleles (0.4%) were discordant and 24 (3.0%) failed to call, while 4 alleles (0.4%) were discordant using HLA-Genotyper. Tumor exomes were also evaluated and were 85.4%, 91.6%, and 100% concordant (Omixon and HLA-Genotyper with 96 alleles tested, and Optitype with 48 class I alleles, respectively). The 15 exomes and 500 pharmacogenomic panels were 100% concordant for each pharmacogenomic allele tested. This work has broad implications spanning future clinical care (pharmacogenomics, tumor response to immunotherapy, autoimmunity, etc.) and research applications.

Patient-specific multi-omics models and the application in personalized combination therapy

The rapid advancement of high-throughput technologies and sharp decrease in cost have opened up the possibility to generate large amount of multi-omics data on an individual basis. The development of high-throughput -omics, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and microbiomics, enables the application of multi-omics technologies in the clinical settings. Combination therapy, defined as disease treatment with two or more drugs to achieve efficacy with lower doses or lower drug toxicity, is the basis for the care of diseases like cancer. Patient-specific multi-omics data integration can help the identification and development of combination therapies. In this review, we provide an overview of different -omics platforms, and discuss the methods for multi-omics, high-throughput, data integration, personalized combination therapy.

Breast Cancer: A Molecularly Heterogenous Disease Needing Subtype-Specific Treatments

Breast cancer is the most commonly occurring cancer in women. There were over two-million new cases in world in 2018. It is the second leading cause of death from cancer in western countries. At the molecular level, breast cancer is a heterogeneous disease, which is characterized by high genomic instability evidenced by somatic gene mutations, copy number alterations, and chromosome structural rearrangements. The genomic instability is caused by defects in DNA damage repair, transcription, DNA replication, telomere maintenance and mitotic chromosome segregation. According to molecular features, breast cancers are subdivided in subtypes, according to activation of hormone receptors (estrogen receptor and progesterone receptor), of human epidermal growth factors receptor 2 (HER2), and or BRCA mutations. In-depth analyses of the molecular features of primary and metastatic breast cancer have shown the great heterogeneity of genetic alterations and their clonal evolution during disease development. These studies have contributed to identify a repertoire of numerous disease-causing genes that are altered through different mutational processes. While early-stage breast cancer is a curable disease in about 70% of patients, advanced breast cancer is largely incurable. However, molecular studies have contributed to develop new therapeutic approaches targeting HER2, CDK4/6, PI3K, or involving poly(ADP-ribose) polymerase inhibitors for BRCA mutation carriers and immunotherapy.

Establishment of chemosensitivity tests in triple-negative and BRCA-mutated breast cancer patient-derived xenograft models

Purpose

A patient-derived xenograft (PDX) model is an in vivo animal model which provides biological and genomic profiles similar to a primary tumor. The characterization of factors that influence the establishment of PDX is crucial. Furthermore, PDX models can provide a platform for chemosensitivity tests to evaluate the effectiveness of a target agent before applying it in clinical trials.

Methods

We implanted 83 cases of breast cancer into NOD.Cg-Prkdcscid Il2rgtm1Sug/Jic mice, to develop PDX models. Clinicopathological factors of primary tumors were reviewed to identify the factors affecting engraftment success rates. After the establishment of PDX models, we performed olaparib and carboplatin chemosensitivity tests. We used PDX models from triple-negative breast cancer (TNBC) with neoadjuvant chemotherapy and/or germline BRCA1 mutations in chemosensitivity tests.

Results

The univariate analyses (p<0.05) showed factors which were significantly associated with successful engraftment of PDX models include poor histologic grade, presence of BRCA mutation, aggressive diseases, and death. Factors which were independently associated with successful engraftment of PDX models on multivariate analyses include poor histologic grade and aggressive diseases status. In chemosensitivity tests, a PDX model with the BRCA1 L1780P mutation showed partial response to olaparib and complete response to carboplatin.

Conclusions

Successful engraftment of PDX models was significantly associated with aggressive diseases. Patients who have aggressive diseases status, large tumors, and poor histologic grade are ideal candidates for developing successful PDX models. Chemosensitivity tests using the PDX models provide additional information about alternative treatment strategies for residual TNBC after neoadjuvant chemotherapy.

Chemotherapy-induced senescent cancer cells engulf other cells to enhance their survival

In chemotherapy-treated breast cancer, wild-type p53 preferentially induces senescence over apoptosis, resulting in a persisting cell population constituting residual disease that drives relapse and poor patient survival via the senescence-associated secretory phenotype. Understanding the properties of tumor cells that allow survival after chemotherapy treatment is paramount. Using time-lapse and confocal microscopy to observe interactions of cells in treated tumors, we show here that chemotherapy-induced senescent cells frequently engulf both neighboring senescent or nonsenescent tumor cells at a remarkable frequency. Engulfed cells are processed through the lysosome and broken down, and cells that have engulfed others obtain a survival advantage. Gene expression analysis showed a marked up-regulation of conserved macrophage-like program of engulfment in chemotherapy-induced senescent cell lines and tumors. Our data suggest compelling explanations for how senescent cells persist in dormancy, how they manage the metabolically expensive process of cytokine production that drives relapse in those tumors that respond the worst, and a function for their expanded lysosomal compartment.

PANOPLY: Omics-Guided Drug Prioritization Method Tailored to an Individual Patient

PURPOSE

The majority of patients with cancer receive treatments that are minimally informed by omics data. We propose a precision medicine computational framework, PANOPLY (Precision Cancer Genomic Report: Single Sample Inventory), to identify and prioritize drug targets and cancer therapy regimens.

MATERIALS AND METHODS

The PANOPLY approach integrates clinical data with germline and somatic features obtained from multiomics platforms and applies machine learning and network analysis approaches in the context of the individual patient and matched controls. The PANOPLY workflow uses the following four steps: selection of matched controls to the patient of interest; identification of patient-specific genomic events; identification of suitable drugs using the driver-gene network and random forest analyses; and provision of an integrated multiomics case report of the patient with prioritization of anticancer drugs.

RESULTS

The PANOPLY workflow can be executed on a stand-alone virtual machine and is also available for download as an R package. We applied the method to an institutional breast cancer neoadjuvant chemotherapy study that collected clinical and genomic data as well as patient-derived xenografts to investigate the prioritization offered by PANOPLY. In a chemotherapy-resistant patient-derived xenograft model, we found that that the prioritized drug, olaparib, was more effective than placebo in treating the tumor ( P < .05). We also applied PANOPLY to in-house and publicly accessible multiomics tumor data sets with therapeutic response or survival data available.

CONCLUSION

PANOPLY shows promise as a means to prioritize drugs on the basis of clinical and multiomics data for an individual patient with cancer. Additional studies are needed to confirm this approach.

A Transcriptionally Definable Subgroup of Triple-Negative Breast and Ovarian Cancer Samples Shows Sensitivity to HSP90 Inhibition

PURPOSE

We hypothesized that integrated analysis of cancer types from different lineages would reveal novel molecularly defined subgroups with unique therapeutic vulnerabilities. On the basis of the molecular similarities between subgroups of breast and ovarian cancers, we analyzed these cancers as a single cohort to test our hypothesis.

EXPERIMENTAL DESIGN

Identification of transcriptional subgroups of cancers and drug sensitivity analyses were performed using mined data. Cell line sensitivity to Hsp90 inhibitors (Hsp90i) was tested in vitro. The ability of a transcriptional signature to predict Hsp90i sensitivity was validated using cell lines, and cell line- and patient-derived xenograft (PDX) models. Mechanisms of Hsp90i sensitivity were uncovered using immunoblot and RNAi.

RESULTS

Transcriptomic analyses of breast and ovarian cancer cell lines uncovered two mixed subgroups comprised primarily of triple-negative breast and multiple ovarian cancer subtypes. Drug sensitivity analyses revealed that cells of one mixed subgroup are significantly more sensitive to Hsp90i compared with cells from all other cancer lineages evaluated. A gene expression classifier was generated that predicted Hsp90i sensitivity in vitro, and in cell line- and PDXs. Cells from the Hsp90i-sensitive subgroup underwent apoptosis mediated by Hsp90i-induced upregulation of the proapoptotic proteins Bim and PUMA.

CONCLUSIONS

Our findings identify Hsp90i as a potential therapeutic strategy for a transcriptionally defined subgroup of ovarian and breast cancers. This study demonstrates that gene expression profiles may be useful to identify therapeutic vulnerabilities in tumor types with limited targetable genetic alterations, and to identify molecularly definable cancer subgroups that transcend lineage.

Chromosome 12p Amplification in Triple-Negative/BRCA1-Mutated Breast Cancer Associates with Emergence of Docetaxel Resistance and Carboplatin Sensitivity

Taxanes are the mainstay of treatment in triple-negative breast cancer (TNBC), with de novo and acquired resistance limiting patient's survival. To investigate the genetic basis of docetaxel resistance in TNBC, exome sequencing was performed on matched TNBC patient-derived xenografts (PDX) sensitive to docetaxel and their counterparts that developed resistance in vivo upon continuous drug exposure. Most mutations, small insertions/deletions, and copy number alterations detected in the initial TNBC human metastatic samples were maintained after serial passages in mice and emergence of resistance. We identified a chromosomal amplification of chr12p in a human BRCA1-mutated metastatic sample and the derived chemoresistant PDX, but not in the matched docetaxel-sensitive PDX tumor. Chr12p amplification was validated in a second pair of docetaxel-sensitive/resistant BRCA1-mutated PDXs and after short-term docetaxel treatment in several TNBC/BRCA1-mutated PDXs and cell lines, as well as during metastatic recurrence in a patient with BRCA1-mutated breast cancer who had progressed on docetaxel treatment. Analysis of clinical data indicates an association between chr12p amplification and patients with TNBC/basal-like breast cancer, a BRCA1 mutational signature, and poor survival after chemotherapy. Detection of chr12p amplification in a cohort of TNBC PDX models was associated with an improved response to carboplatin. Our findings reveal tumor clonal dynamics during chemotherapy treatments and suggest that a preexisting population harboring chr12p amplification is associated with the emergence of docetaxel resistance and carboplatin responsiveness in TNBC/BRCA1-mutated tumors. SIGNIFICANCE: Chr12p copy number gains indicate rapid emergence of resistance to docetaxel and increased sensitivity to carboplatin, therefore sequential docetaxel/carboplatin treatment could improve survival in TNBC/BRCA1 patients. GRAPHICAL ABSTRACT: http://cancerres.aacrjournals.org/content/canres/79/16/4258/F1.large.jpg.

KPNA3 Confers Sorafenib Resistance to Advanced Hepatocellular Carcinoma via TWIST Regulated Epithelial-Mesenchymal Transition

Sorafenib, a multikinase inhibitor, is a new standard treatment for patients with advanced hepatocellular carcinoma (HCC). However, resistance to this regimen is frequently observed in clinical practice, and the molecular basis of this resistance remains largely unknown. Herein, the antitumor activity of sorafenib was assessed in 16 patient-derived xenograft (PDX) models of HCC. Gene expression analysis was conducted to identify factors that promote sorafenib resistance. Quantitative RT-PCR and immunoblotting were used to determine gene expression and activation of signaling pathways. Cell proliferation, clone formation, and transwell assays were conducted to evaluate drug-sensitivity, proliferation, and invasiveness, respectively. Kaplan-Meier analysis was used to evaluate the predictive power of biomarkers for sorafenib response. Differential gene expression analysis suggested that sorafenib resistance correlated with high karyopherin subunit alpha 3 (KPNA3) expression. Overexpression of KPNA3 in HCC cells enhanced tumor cell growth and invasiveness. Interestingly, KPNA3 was found to trigger epithelial-mesenchymal transition (EMT), a key process mediating drug resistance. On a mechanistic level, KPNA3 increased phosphorylation of AKT, which then phosphorylated ERK, and ultimately promoted TWIST expression to induce EMT and sorafenib resistance. Moreover, retrospective analysis revealed that HCC patients with low KPNA3 expression had remarkably longer survival after sorafenib treatment. Finally, we have identified a novel KPNA3-AKT-ERK-TWIST signaling cascade that promotes EMT and mediates sorafenib resistance in HCC. These findings suggest that KPNA3 is a promising biomarker for predicting patient responsiveness to sorafenib. Targeting KPNA3 may also contribute to resolving sorafenib resistance in HCC.

Patient-Derived Xenograft Models of Breast Cancer and Their Application

Recently, patient-derived xenograft (PDX) models of many types of tumors including breast cancer have emerged as a powerful tool for predicting drug efficacy and for understanding tumor characteristics. PDXs are established by the direct transfer of human tumors into highly immunodeficient mice and then maintained by passaging from mouse to mouse. The ability of PDX models to maintain the original features of patient tumors and to reflect drug sensitivity has greatly improved both basic and clinical study outcomes. However, current PDX models cannot completely predict drug efficacy because they do not recapitulate the tumor microenvironment of origin, a failure which puts emphasis on the necessity for the development of the next generation PDX models. In this article, we summarize the advantages and limitations of current PDX models and discuss the future directions of this field.

GECKO is a genetic algorithm to classify and explore high throughput sequencing data

Comparative analysis of high throughput sequencing data between multiple conditions often involves mapping of sequencing reads to a reference and downstream bioinformatics analyses. Both of these steps may introduce heavy bias and potential data loss. This is especially true in studies where patient transcriptomes or genomes may vary from their references, such as in cancer. Here we describe a novel approach and associated software that makes use of advances in genetic algorithms and feature selection to comprehensively explore massive volumes of sequencing data to classify and discover new sequences of interest without a mapping step and without intensive use of specialized bioinformatics pipelines. We demonstrate that our approach called GECKO for GEnetic Classification using k-mer Optimization is effective at classifying and extracting meaningful sequences from multiple types of sequencing approaches including mRNA, microRNA, and DNA methylome data.

Spontaneous murine tumors in the development of patient-derived xenografts: a potential pitfall

Patient-derived xenografts (PDX) are generated in immune deficient mice and demonstrate histologic and molecular features similar to their corresponding human tumors. However, murine tumors (non-human) spontaneously occur in these models. 120 consecutive patients with high-risk primary breast cancer enrolled in the prospective neoadjuvant BEAUTY study had tumor tissue obtained at the time of diagnosis. These tumor cells, including initial tissue and subsequent generations, were injected into either NSG (n = 365) or NOD-SCID (n = 396) female mice. Mice with initial tumor growth sufficient for transfer to the 2nd generation underwent histologic review by pathologists, including Ki67 staining. After passaging the tumors for up to 4 generations, at least one primary mouse tumor was detected from 24 of the 54 PDX-lines, for a frequency of 3.2% (24 mice out of 761 mice), including murine lymphomas (n = 13), mammary tumors (n = 7), osteosarcomas (n = 2), and hemangiosarcomas (n = 2). While true PDX showed scattered strong staining with Ki67, murine tumors were Ki67 negative. No significant differences (p = 0.062) were observed comparing development of murine tumors in NOD-SCID (n = 8) vs NSG mice (n = 16). While PDX are a useful tool in cancer research, there is a potential for spontaneous murine tumors to arise, which could alter results of studies utilizing PDX. Morphologic review by a pathologist, potentially along with Ki67 staining, is necessary to ensure that tumor growth represents the desired PDX prior to use in downstream studies. This study is the first prospective study evaluating the frequency, type, and time frame for development of non-human tumors.

Comparison of 99mTc-Sestamibi Molecular Breast Imaging and Breast MRI in Patients With Invasive Breast Cancer Receiving Neoadjuvant Chemotherapy

OBJECTIVE. The purpose of this study is to prospectively compare the size of invasive breast cancer before and after neoadjuvant chemotherapy (NAC) at breast MRI and molecular breast imaging (MBI) and to assess the accuracy of post-NAC MBI and MRI relative to pathologic analysis. SUBJECTS AND METHODS. Women with invasive breast cancer greater than or equal to 1.5 cm were enrolled to compare the longest dimension before and after NAC at MRI and MBI. MBI was performed on a dual-detector cadmium zinc telluride system after administration of 6.5 mCi (240 MBq) ^99mTc-sestamibi. The accuracy of MRI and MBI in assessing residual disease (invasive disease or ductal carcinoma in situ) was determined relative to pathologic examination. RESULTS. The longest dimension at MRI was within 1.0 cm of that at MBI in 72.3% of cases before NAC and 70.1% of cases after NAC. The difference between the longest dimension at imaging after NAC and pathologic tumor size was within 1 cm for 58.7% of breast MRI cases and 59.6% of MBI cases. Ninety patients underwent both MRI and MBI after NAC. In the 56 patients with invasive residual disease, 10 (17.9%) cases were negative at MRI and 23 (41.1%) cases were negative at MBI. In the 34 patients with breast pathologic complete response, there was enhancement in 10 cases (29.4%) at MRI and uptake in six cases (17.6%) at MBI. Sensitivity, specificity, positive predictive value, and negative predictive value after NAC were 82.8%, 69.4%, 81.4%, and 71.4%, respectively, for MRI and 58.9%, 82.4%, 84.6%, and 54.9%, respectively, for MBI. CONCLUSION. Breast MRI and MBI showed similar disease extent before NAC. MBI may be an alternative to breast MRI in patients with a contraindication to breast MRI. Neither modality showed sufficient accuracy after NAC in predicting breast pathologic complete response to obviate tissue diagnosis to assess for residual invasive disease. Defining the extent of residual disease compared with pathologic evaluation was also limited after NAC for both breast MRI and MBI.

Post-neoadjuvant treatment and the management of residual disease in breast cancer: state of the art and perspectives

Achieving a pathologic complete response after neoadjuvant treatment is associated with improved prognosis in breast cancer. The CREATE-X trial demonstrated a significant survival improvement with capecitabine in patients with residual invasive disease after neoadjuvant chemotherapy, and the KATHERINE trial showed a significant benefit of trastuzumab-emtansine (TDM1) in human epidermal growth factor receptor 2 (HER2)-positive patients who did not achieve a pathologic complete response after neoadjuvant treatment, creating interesting alternatives of post-neoadjuvant treatments for high-risk patients. New agents are arising as therapeutic options for metastatic breast cancer such as the cyclin-dependent kinase inhibitors and the immune-checkpoint inhibitors, but none has been incorporated into the post-neoadjuvant setting so far. Evolving techniques such as next-generation sequencing and gene expression profiles have improved our knowledge regarding the biology of residual disease, and also on the mechanisms involved in treatment resistance. The present manuscript reviews the current available strategies, the ongoing trials, the potential biomarker-guided approaches and the perspectives for the post-neoadjuvant treatment and the management of residual disease after neoadjuvant treatment in breast cancer.

The novel function of tumor protein D54 in regulating pyruvate dehydrogenase and metformin cytotoxicity in breast cancer

Background

The role of tumor protein D54 in breast cancer has not been studied and its function in breast cancer remains unclear. In our previous pharmacogenomic studies using lymphoblastoid cell line (LCL), this protein has been identified to affect metformin response. Although metformin has been widely studied as a prophylactic and chemotherapeutic drug, there is still a lack of biomarkers predicting the response to metformin in breast cancer. In this study, we revealed the novel function of TPD54 in breast cancer through understanding how TPD54 altered the cancer cell sensitivity to metformin.

Methods

The role of TPD54 in altering cellular sensitivity to metformin treatment was carried out by either knockdown or overexpression of TPD54, followed by measuring cell viability and reactive oxygen species (ROS) production in MCF7 breast cancer cell line and breast cancer patient-derived xenografts. Functional analysis of TPD54 in breast cancer cells was demonstrated by studying TPD54 protein localization and identification of potential binding partners of TPD54 through immunoprecipitation followed by mass spectrometry. The effect of TPD54 on pyruvate dehydrogenase (PDH) protein regulation was demonstrated by western blot, immunoprecipitation, and site-directed mutagenesis.

Results

TPD54 inhibited colony formation and enhanced cellular sensitivity to metformin treatment in MCF7 cells and breast cancer patient-derived xenografts. Mechanistic study indicated that TPD54 had mitochondrial localization, bound to and stabilized pyruvate dehydrogenase E1α by blocking pyruvate dehydrogenase kinase 1 (PDK1)-mediated serine 232 phosphorylation. TPD54 knockdown increased PDH E1α protein degradation and led to decreased PDH enzyme activity, which reduced mitochondrial oxygen consumption and reactive oxygen species (ROS) production, thus contributing to the resistance of breast cancer cells to metformin treatment.

Conclusion

We have discovered a novel mechanism by which TPD54 regulates pyruvate dehydrogenase and affects the sensitivity of breast cancer to metformin treatment. Our findings highlight the important post-translational regulation of PDK1 on PDH E1α and the potential application of TPD54 as a biomarker for selecting tumors that may be sensitive to metformin therapy. These provide new insights into understanding the regulation of PDH complexes and the resistance mechanisms of cancer cells to metformin treatment.

Electronic supplementary material

The online version of this article (10.1186/s40170-018-0193-4) contains supplementary material, which is available to authorized users.

Tyrosine Phosphorylation of Mitochondrial Creatine Kinase 1 Enhances a Druggable Tumor Energy Shuttle Pathway

How mitochondrial metabolism is altered by oncogenic tyrosine kinases to promote tumor growth is incompletely understood. Here, we show that oncogenic HER2 tyrosine kinase signaling induces phosphorylation of mitochondrial creatine kinase 1 (MtCK1) on tyrosine 153 (Y153) in an ABL-dependent manner in breast cancer cells. Y153 phosphorylation, which is commonly upregulated in HER2+ breast cancers, stabilizes MtCK1 to increase the phosphocreatine energy shuttle and promote proliferation. Inhibition of the phosphocreatine energy shuttle by MtCK1 knockdown or with the creatine analog cyclocreatine decreases proliferation of trastuzumab-sensitive and -resistant HER2+ cell lines in culture and in xenografts. Finally, we show that cyclocreatine in combination with the HER2 kinase inhibitor lapatinib reduces the growth of a trastuzumab-resistant HER2+ patient-derived xenograft. These findings suggest that activation of the phosphocreatine energy shuttle by MtCK1 Y153 phosphorylation creates a druggable metabolic vulnerability in cancer.

ERβ-mediated induction of cystatins results in suppression of TGFβ signaling and inhibition of triple-negative breast cancer metastasis

Triple-negative breast cancer (TNBC) accounts for a disproportionately high number of deaths due to a lack of targeted therapies and an increased likelihood of distant recurrence. Estrogen receptor beta (ERβ), a well-characterized tumor suppressor, is expressed in 30% of TNBCs, and its expression is associated with improved patient outcomes. We demonstrate that therapeutic activation of ERβ elicits potent anticancer effects in TNBC through the induction of a family of secreted proteins known as the cystatins, which function to inhibit canonical TGFβ signaling and suppress metastatic phenotypes both in vitro and in vivo. These data reveal the involvement of cystatins in suppressing breast cancer progression and highlight the value of ERβ-targeted therapies for the treatment of TNBC patients.

ATR Inhibition Is a Promising Radiosensitizing Strategy for Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is characterized by elevated locoregional recurrence risk despite aggressive local therapies. New tumor-specific radiosensitizers are needed. We hypothesized that the ATR inhibitor, VX-970 (now known as M6620), would preferentially radiosensitize TNBC. Noncancerous breast epithelial and TNBC cell lines were investigated in clonogenic survival, cell cycle, and DNA damage signaling and repair assays. In addition, patient-derived xenograft (PDX) models generated prospectively as part of a neoadjuvant chemotherapy study from either baseline tumor biopsies or surgical specimens with chemoresistant residual disease were assessed for sensitivity to fractionated radiotherapy, VX-970, or the combination. To explore potential response biomarkers, exome sequencing was assessed for germline and/or somatic alterations in homologous recombination (HR) genes and other alterations associated with ATR inhibitor sensitivity. VX-970 preferentially inhibited ATR-Chk1-CDC25a signaling, abrogated the radiotherapy-induced G₂-M checkpoint, delayed resolution of DNA double-strand breaks, and reduced colony formation after radiotherapy in TNBC cells relative to normal-like breast epithelial cells. In vivo, VX-970 did not exhibit significant single-agent activity at the dose administered even in the context of genomic alterations predictive of ATR inhibitor responsiveness, but significantly sensitized TNBC PDXs to radiotherapy. Exome sequencing and functional testing demonstrated that combination therapy was effective in both HR-proficient and -deficient models. PDXs established from patients with chemoresistant TNBC were also highly radiosensitized. In conclusion, VX-970 is a tumor-specific radiosensitizer for TNBC. Patients with residual TNBC after neoadjuvant chemotherapy, a subset at particularly high risk of relapse, may be ideally suited for this treatment intensification strategy. Mol Cancer Ther; 17(11); 2462-72. ©2018 AACR.

A Population of Heterogeneous Breast Cancer Patient-Derived Xenografts Demonstrate Broad Activity of PARP Inhibitor in BRCA1/2 Wild-Type Tumors

Background: Breast cancer patients who do not respond to neoadjuvant therapy have a poor prognosis. There is a pressing need for novel targets and models for preclinical testing. Here we report characterization of breast cancer patient-derived xenografts (PDX) largely generated from residual tumors following neoadjuvant chemotherapy.Experimental Design: PDXs were derived from surgical samples of primary or locally recurrent tumors. Normal and tumor DNA sequencing, RNASeq, and reverse phase protein arrays (RPPA) were performed. Phenotypic profiling was performed by determining efficacy of a panel of standard and investigational agents.Results: Twenty-six PDXs were developed from 25 patients. Twenty-two were generated from residual disease following neoadjuvant chemotherapy, and 24 were from triple-negative breast cancer (TNBC). These PDXs harbored a heterogeneous set of genomic alterations and represented all TNBC molecular subtypes. On RPPA, PDXs varied in extent of PI3K and MAPK activation. PDXs also varied in their sensitivity to chemotherapeutic agents. PI3K, mTOR, and MEK inhibitors repressed growth but did not cause tumor regression. The PARP inhibitor talazoparib caused dramatic regression in five of 12 PDXs. Notably, four of five talazoparib-sensitive models did not harbor germline BRCA1/2 mutations, but several had somatic alterations in homologous repair pathways, including ATM deletion and BRCA2 alterations.Conclusions: PDXs capture the molecular and phenotypic heterogeneity of TNBC. Here we show that PARP inhibition can have activity beyond germline BRCA1/2 altered tumors, causing regression in a variety of molecular subtypes. These models represent an opportunity for the discovery of rational combinations with targeted therapies and predictive biomarkers. Clin Cancer Res; 23(21); 6468-77. ©2017 AACR.

DNA methyltransferase expression in triple-negative breast cancer predicts sensitivity to decitabine

Triple-negative breast cancer (TNBC) is a heterogeneous disease with poor prognosis that lacks targeted therapies, especially in patients with chemotherapy-resistant disease. Since DNA methylation-induced silencing of tumor suppressors is common in cancer, reversal of promoter DNA hypermethylation by 5-aza-2'-deoxycytidine (decitabine), an FDA-approved DNA methyltransferase (DNMT) inhibitor, has proven effective in treating hematological neoplasms. However, its antitumor effect varies in solid tumors, stressing the importance of identifying biomarkers predictive of therapeutic response. Here, we focused on the identification of biomarkers to select decitabine-sensitive TNBC through increasing our understanding of the mechanism of decitabine action. We showed that protein levels of DNMTs correlated with response to decitabine in patient-derived xenograft (PDX) organoids originating from chemotherapy-sensitive and -resistant TNBCs, suggesting DNMT levels as potential biomarkers of response. Furthermore, all 3 methytransferases, DNMT1, DNMT3A, and DNMT3B, were degraded following low-concentration, long-term decitabine treatment both in vitro and in vivo. The DNMT proteins could be ubiquitinated by the E3 ligase, TNF receptor-associated factor 6 (TRAF6), leading to lysosome-dependent protein degradation. Depletion of TRAF6 blocked decitabine-induced DNMT degradation, conferring resistance to decitabine. Our study suggests a potential mechanism of regulating DNMT protein degradation and DNMT levels as response biomarkers for DNMT inhibitors in TNBCs.

Discovery of a Glucocorticoid Receptor (GR) Activity Signature Using Selective GR Antagonism in ER-Negative Breast Cancer

Purpose: Although high glucocorticoid receptor (GR) expression in early-stage estrogen receptor (ER)-negative breast cancer is associated with shortened relapse-free survival (RFS), how associated GR transcriptional activity contributes to aggressive breast cancer behavior is not well understood. Using potent GR antagonists and primary tumor gene expression data, we sought to identify a tumor-relevant gene signature based on GR activity that would be more predictive than GR expression alone.Experimental Design: Global gene expression and GR ChIP-sequencing were performed to identify GR-regulated genes inhibited by two chemically distinct GR antagonists, mifepristone and CORT108297. Differentially expressed genes from MDA-MB-231 cells were cross-evaluated with significantly expressed genes in GR-high versus GR-low ER-negative primary breast cancers. The resulting subset of GR-targeted genes was analyzed in two independent ER-negative breast cancer cohorts to derive and then validate the GR activity signature (GRsig).Results: Gene expression pathway analysis of glucocorticoid-regulated genes (inhibited by GR antagonism) revealed cell survival and invasion functions. GR ChIP-seq analysis demonstrated that GR antagonists decreased GR chromatin association for a subset of genes. A GRsig that comprised n = 74 GR activation-associated genes (also reversed by GR antagonists) was derived from an adjuvant chemotherapy-treated Discovery cohort and found to predict probability of relapse in a separate Validation cohort (HR = 1.9; P = 0.012).Conclusions: The GRsig discovered herein identifies high-risk ER-negative/GR-positive breast cancers most likely to relapse despite administration of adjuvant chemotherapy. Because GR antagonism can reverse expression of these genes, we propose that addition of a GR antagonist to chemotherapy may improve outcome for these high-risk patients. Clin Cancer Res; 24(14); 3433-46. ©2018 AACR.

Differential roles of ERRFI1 in EGFR and AKT pathway regulation affect cancer proliferation

AKT signaling is modulated by a complex network of regulatory proteins and is commonly deregulated in cancer. Here, we present a dual mechanism of AKT regulation by the ERBB receptor feedback inhibitor 1 (ERRFI1). We show that in cells expressing high levels of EGFR, ERRF1 inhibits growth and enhances responses to chemotherapy. This is mediated in part through the negative regulation of AKT signaling by direct ERRFI1-dependent inhibition of EGFR In cells expressing low levels of EGFR, ERRFI1 positively modulates AKT signaling by interfering with the interaction of the inactivating phosphatase PHLPP with AKT, thereby promoting cell growth and chemotherapy desensitization. These observations broaden our understanding of chemotherapy response and have important implications for the selection of targeted therapies in a cell context-dependent manner. EGFR inhibition can only sensitize EGFR-high cells for chemotherapy, while AKT inhibition increases chemosensitivity in EGFR-low cells. By understanding these mechanisms, we can take advantage of the cellular context to individualize antineoplastic therapy. Finally, our data also suggest targeting of EFFRI1 in EGFR-low cancer as a promising therapeutic approach.