Pharmacological targeting of netrin-1 inhibits EMT in cancer.

Epithelial-to-mesenchymal transition (EMT) regulates tumour initiation, progression, metastasis and resistance to anti-cancer therapy1-7. Although great progress has been made in understanding the role of EMT and its regulatory mechanisms in cancer, no therapeutic strategy to pharmacologically target EMT has been identified. Here we found that netrin-1 is upregulated in a primary mouse model of skin squamous cell carcinoma (SCC) exhibiting spontaneous EMT. Pharmacological inhibition of netrin-1 by administration of NP137, a netrin-1-blocking monoclonal antibody currently used in clinical trials in human cancer (ClinicalTrials.gov identifier NCT02977195 ), decreased the proportion of EMT tumour cells in skin SCC, decreased the number of metastases and increased the sensitivity of tumour cells to chemotherapy. Single-cell RNA sequencing revealed the presence of different EMT states, including epithelial, early and late hybrid EMT, and full EMT states, in control SCC. By contrast, administration of NP137 prevented the progression of cancer cells towards a late EMT state and sustained tumour epithelial states. Short hairpin RNA knockdown of netrin-1 and its receptor UNC5B in EPCAM+ tumour cells inhibited EMT in vitro in the absence of stromal cells and regulated a common gene signature that promotes tumour epithelial state and restricts EMT. To assess the relevance of these findings to human cancers, we treated mice transplanted with the A549 human cancer cell line-which undergoes EMT following TGFß1 administration8,9-with NP137. Netrin-1 inhibition decreased EMT in these transplanted A549 cells. Together, our results identify a pharmacological strategy for targeting EMT in cancer, opening up novel therapeutic interventions for anti-cancer therapy.

Imprint of parity and age at first pregnancy on the genomic landscape of subsequent breast cancer.

BACKGROUND: Although parity and age at first pregnancy are among the most known extrinsic factors that modulate breast cancer risk, their impact on the biology of subsequent breast cancer has never been explored in depth. Recent data suggest that pregnancy-induced tumor protection is different according to breast cancer subtypes, with parity and young age at first pregnancy being associated with a marked reduction in the risk of developing luminal subtype but not triple negative breast cancer. In this study, we investigated the imprint of parity and age at first pregnancy on the pattern of somatic mutations, somatic copy number alterations, transcriptomic profiles, and tumor immune microenvironment by assessing tumor-infiltrating lymphocytes (TILs) levels of subsequent breast cancer. METHODS: A total of 313 patients with primary breast cancer with available whole genome, RNA sequencing, and TILs data were included in this study. We used a multivariate analysis adjusted for age at diagnosis, pathological stage, molecular subtypes, and histological subtypes. We compared nulliparous vs. parous, late parous vs. early parous, and nulliparous vs. pregnancy-associated breast cancer (PABC) patients. Late and early parous patients were grouped by using the median age at first pregnancy. PABC was defined as patients diagnosed up to 10 years postpartum. RESULTS: Genomic alterations of breast cancer were associated with age at first pregnancy but not with parity status alone. Independently of clinicopathological features, early parous patients developed tumors characterized by a higher number of Indels (Padj = 0.002), a lower frequency of CDH1 mutations (1.2% vs. 12.7%; Padj = 0.013), a higher frequency of TP53 mutations (50% vs. 22.5%; Padj = 0.010), and MYC amplification (28% vs. 7%; Padj = 0.008). PABC were associated with increased TILs infiltration (Padj = 0.0495). CONCLUSIONS: These findings highlight an unprecedented link between reproductive history and the genomic landscape of subsequent breast cancer. We further hypothesize that TP53-mutant premalignant lesions could be less susceptible to the protective effect of an early parity, which might explain the difference of parity-induced protection according to breast cancer subtypes. This work also advocates that reproductive history should be routinely collected in future large-scale genomic studies addressing the biology of female cancers.

Detection of atypical data in multicenter clinical trials using unsupervised statistical monitoring.

BACKGROUND/AIMS: A risk-based approach to clinical research may include a central statistical assessment of data quality. We investigated the operating characteristics of unsupervised statistical monitoring aimed at detecting atypical data in multicenter experiments. The approach is premised on the assumption that, save for random fluctuations and natural variations, data coming from all centers should be comparable and statistically consistent. Unsupervised statistical monitoring consists of performing as many statistical tests as possible on all trial data, in order to detect centers whose data are inconsistent with data from other centers. METHODS: We conducted simulations using data from a large multicenter trial conducted in Japan for patients with advanced gastric cancer. The actual trial data were contaminated in computer simulations for varying percentages of centers, percentages of patients modified within each center and numbers and types of modified variables. The unsupervised statistical monitoring software was run by a blinded team on the contaminated data sets, with the purpose of detecting the centers with contaminated data. The operating characteristics (sensitivity, specificity and Youden's J-index) were calculated for three detection methods: one using the p-values of individual statistical tests after adjustment for multiplicity, one using a summary of all p-values for a given center, called the Data Inconsistency Score, and one using both of these methods. RESULTS: The operating characteristics of the three methods were satisfactory in situations of data contamination likely to occur in practice, specifically when a single or a few centers were contaminated. As expected, the sensitivity increased for increasing proportions of patients and increasing numbers of variables contaminated. The three methods showed a specificity better than 93% in all scenarios of contamination. The method based on the Data Inconsistency Score and individual p-values adjusted for multiplicity generally had slightly higher sensitivity at the expense of a slightly lower specificity. CONCLUSIONS: The use of brute force (a computer-intensive approach that generates large numbers of statistical tests) is an effective way to check data quality in multicenter clinical trials. It can provide a cost-effective complement to other data-management and monitoring techniques.

Statistical monitoring of data quality and consistency in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial.

INTRODUCTION: Data quality may impact the outcome of clinical trials; hence, there is a need to implement quality control strategies for the data collected. Traditional approaches to quality control have primarily used source data verification during on-site monitoring visits, but these approaches are hugely expensive as well as ineffective. There is growing interest in central statistical monitoring (CSM) as an effective way to ensure data quality and consistency in multicenter clinical trials. METHODS: CSM with SMART™ uses advanced statistical tools that help identify centers with atypical data patterns which might be the sign of an underlying quality issue. This approach was used to assess the quality and consistency of the data collected in the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial, involving 1495 patients across 232 centers in Japan. RESULTS: In the Stomach Cancer Adjuvant Multi-institutional Trial Group Trial, very few atypical data patterns were found among the participating centers, and none of these patterns were deemed to be related to a quality issue that could significantly affect the outcome of the trial. DISCUSSION: CSM can be used to provide a check of the quality of the data from completed multicenter clinical trials before analysis, publication, and submission of the results to regulatory agencies. It can also form the basis of a risk-based monitoring strategy in ongoing multicenter trials. CSM aims at improving data quality in clinical trials while also reducing monitoring costs.

Data-driven risk identification in phase III clinical trials using central statistical monitoring.

Our interest lies in quality control for clinical trials, in the context of risk-based monitoring (RBM). We specifically study the use of central statistical monitoring (CSM) to support RBM. Under an RBM paradigm, we claim that CSM has a key role to play in identifying the "risks to the most critical data elements and processes" that will drive targeted oversight. In order to support this claim, we first see how to characterize the risks that may affect clinical trials. We then discuss how CSM can be understood as a tool for providing a set of data-driven key risk indicators (KRIs), which help to organize adaptive targeted monitoring. Several case studies are provided where issues in a clinical trial have been identified thanks to targeted investigation after the identification of a risk using CSM. Using CSM to build data-driven KRIs helps to identify different kinds of issues in clinical trials. This ability is directly linked with the exhaustiveness of the CSM approach and its flexibility in the definition of the risks that are searched for when identifying the KRIs. In practice, a CSM assessment of the clinical database seems essential to ensure data quality. The atypical data patterns found in some centers and variables are seen as KRIs under a RBM approach. Targeted monitoring or data management queries can be used to confirm whether the KRIs point to an actual issue or not.

Constitutive phosphorylated STAT3-associated gene signature is predictive for trastuzumab resistance in primary HER2-positive breast cancer.

BACKGROUND: The likelihood of recurrence in patients with breast cancer who have HER2-positive tumors is relatively high, although trastuzumab is a remarkably effective drug in this setting. Signal transducer and activator of transcription 3 protein (STAT3), a transcription factor that is persistently tyrosine-705 phosphorylated (pSTAT3) in response to numerous oncogenic signaling pathways, activates downstream proliferative and anti-apoptotic pathways. We hypothesized that pSTAT3 expression in HER2-positive breast cancer will confer trastuzumab resistance. METHODS: We integrated reverse phase protein array (RPPA) and gene expression data from patients with HER2-positive breast cancer treated with trastuzumab in the adjuvant setting. RESULTS: We show that a pSTAT3-associated gene signature (pSTAT3-GS) is able to predict pSTAT3 status in an independent dataset (TCGA; AUC = 0.77, P = 0.02). This suggests that STAT3 induces a characteristic set of gene expression changes in HER2-positive cancers. Tumors characterized as high pSTAT3-GS were associated with trastuzumab resistance (log rank P = 0.049). These results were confirmed using data from the prospective, randomized controlled FinHer study, where the effect was especially prominent in HER2-positive estrogen receptor (ER)-negative tumors (interaction test P = 0.02). Of interest, constitutively activated pSTAT3 tumors were associated with loss of PTEN, elevated IL6, and stromal reactivation. CONCLUSIONS: This study provides compelling evidence for a link between pSTAT3 and trastuzumab resistance in HER2-positive primary breast cancers. Our results suggest that it may be valuable to add agents targeting the STAT3 pathway to trastuzumab for treatment of HER2-positive breast cancer.

Tumor Intrinsic Subtypes and Gene Expression Signatures in Early-Stage ERBB2/HER2-Positive Breast Cancer: A Pooled Analysis of CALGB 40601, NeoALTTO, and NSABP B-41 Trials.

Importance: Biologic features may affect pathologic complete response (pCR) and event-free survival (EFS) after neoadjuvant chemotherapy plus ERBB2/HER2 blockade in ERBB2/HER2-positive early breast cancer (EBC). Objective: To define the quantitative association between pCR and EFS by intrinsic subtype and by other gene expression signatures in a pooled analysis of 3 phase 3 trials: CALGB 40601, NeoALTTO, and NSABP B-41. Design, Setting, and Participants: In this retrospective pooled analysis, 1289 patients with EBC received chemotherapy plus either trastuzumab, lapatinib, or the combination, with a combined median follow-up of 5.5 years. Gene expression profiling by RNA sequencing was obtained from 758 samples, and intrinsic subtypes and 618 gene expression signatures were calculated. Data analyses were performed from June 1, 2020, to January 1, 2023. Main Outcomes and Measures: The association of clinical variables and gene expression biomarkers with pCR and EFS were studied by logistic regression and Cox analyses. Results: In the pooled analysis, of 758 women, median age was 49 years, 12% were Asian, 6% Black, and 75% were White. Overall, pCR results were associated with EFS in the ERBB2-enriched (hazard ratio [HR], 0.45; 95% CI, 0.29-0.70; P < .001) and basal-like (HR, 0.19; 95% CI, 0.04-0.86; P = .03) subtypes but not in luminal A or B tumors. Dual trastuzumab plus lapatinib blockade over trastuzumab alone had a trend toward EFS benefit in the intention-to-treat population; however, in the ERBB2-enriched subtype there was a significant and independent EFS benefit of trastuzumab plus lapatinib vs trastuzumab alone (HR, 0.47; 95% CI, 0.27-0.83; P = .009). Overall, 275 of 618 gene expression signatures (44.5%) were significantly associated with pCR and 9 of 618 (1.5%) with EFS. The ERBB2/HER2 amplicon and multiple immune signatures were significantly associated with pCR. Luminal-related signatures were associated with lower pCR rates but better EFS, especially among patients with residual disease and independent of hormone receptor status. There was significant adjusted HR for pCR ranging from 0.45 to 0.81 (higher pCR) and 1.21-1.94 (lower pCR rate); significant adjusted HR for EFS ranged from 0.71 to 0.94. Conclusions and relevance: In patients with ERBB2/HER2-positive EBC, the association between pCR and EFS differed by tumor intrinsic subtype, and the benefit of dual ERBB2/HER2 blockade was limited to ERBB2-enriched tumors. Immune-activated signatures were concordantly associated with higher pCR rates and better EFS, whereas luminal signatures were associated with lower pCR rates.

Predictive Biomarkers for Response to Immunotherapy in Triple Negative Breast Cancer: Promises and Challenges.

Triple negative breast cancer (TNBC) is a highly heterogeneous disease with a poor prognosis and a paucity of therapeutic options. In recent years, immunotherapy has emerged as a new treatment option for patients with TNBC. However, this therapeutic evolution is paralleled by a growing need for biomarkers which allow for a better selection of patients who are most likely to benefit from this immune checkpoint inhibitor (ICI)-based regimen. These biomarkers will not only facilitate a better optimization of treatment strategies, but they will also avoid unnecessary side effects in non-responders, and limit the increasing financial toxicity linked to the use of these agents. Huge efforts have been deployed to identify predictive biomarkers for the ICI, but until now, the fruits of this labor remained largely unsatisfactory. Among clinically validated biomarkers, only programmed death-ligand 1 protein (PD-L1) expression has been prospectively assessed in TNBC trials. In addition to this, microsatellite instability and a high tumor mutational burden are approved as tumor agnostic biomarkers, but only a small percentage of TNBC fits this category. Furthermore, TNBC should no longer be approached as a single biological entity, but rather as a complex disease with different molecular, clinicopathological, and tumor microenvironment subgroups. This review provides an overview of the validated and evolving predictive biomarkers for a response to ICI in TNBC.

Differential Benefit of Metronomic Chemotherapy Among Triple-Negative Breast Cancer Subtypes Treated in the IBCSG Trial 22-00.

PURPOSE: To explore whether specific triple-negative breast cancer (TNBC) molecular subtypes are predictive for a benefit from maintenance low-dose cyclophosphamide and methotrexate (CM) in the adjuvant IBCSG 22-00 phase III clinical trial. EXPERIMENTAL DESIGN: RNA sequencing was performed on a selection of 347 TNBC formalin-fixed paraffin-embedded (FFPE) tumor samples following a case-cohort-like sampling. TNBC subtypes were computed on gene expression data. The association between TNBC subtypes and treatment outcome was assessed using a Cox proportional-hazards interaction test. RESULTS: Immunomodulatory (IM) and basal-like/immune activated (BLIA) molecular subtypes showed a significant survival benefit when treated with low-dose CM [disease-free survival (DFS): HR, 0.5; 95% confidence interval (CI), 0.28-0.89; Pinteraction = 0.018 and HR, 0.49; 95% CI, 0.27-0.9; Pinteraction = 0.021]. Moreover, a high expression of regulatory T-cell immune signature was associated with a better prognosis in the CM arm, in line with a potential immunomodulating role of cyclophosphamide. In contrast, a worse outcome was observed in tumors with a mesenchymal (M) subtype treated with low-dose CM (DFS: HR, 1.9; 95% CI, 1.2-3; Pinteraction = 0.0044). CONCLUSIONS: Our results show a differential benefit of low-dose CM therapy across different TNBC subtypes. Low-dose CM therapy could be considered as a potential strategy for TNBC tumors with IM subtype in the early-disease setting.

Immunological and clinicopathological features predict HER2-positive breast cancer prognosis in the neoadjuvant NeoALTTO and CALGB 40601 randomized trials.

The identification of prognostic markers in patients receiving neoadjuvant therapy is crucial for treatment optimization in HER2-positive breast cancer, with the immune microenvironment being a key factor. Here, we investigate the complexity of B and T cell receptor (BCR and TCR) repertoires in the context of two phase III trials, NeoALTTO and CALGB 40601, evaluating neoadjuvant paclitaxel with trastuzumab and/or lapatinib in women with HER2-positive breast cancer. BCR features, particularly the number of reads and clones, evenness and Gini index, are heterogeneous according to hormone receptor status and PAM50 subtypes. Moreover, BCR measures describing clonal expansion, namely evenness and Gini index, are independent prognostic factors. We present a model developed in NeoALTTO and validated in CALGB 40601 that can predict event-free survival (EFS) by integrating hormone receptor and clinical nodal status, breast pathological complete response (pCR), stromal tumor-infiltrating lymphocyte levels (%) and BCR repertoire evenness. A prognostic score derived from the model and including those variables, HER2-EveNT, allows the identification of patients with 5-year EFS > 90%, and, in those not achieving pCR, of a subgroup of immune-enriched tumors with an excellent outcome despite residual disease.

Paclitaxel plus carboplatin and durvalumab with or without oleclumab for women with previously untreated locally advanced or metastatic triple-negative breast cancer: the randomized SYNERGY phase I/II trial.

Chemo-immunotherapy is the first-line standard of care for patients with PD-L1 positive metastatic triple-negative breast cancer (mTNBC). SYNERGY (NCT03616886) is a dose-finding phase I and a randomized phase II, open-label trial evaluating if targeting the immunosuppressive adenosine pathway can enhance the antitumor activity of chemo-immunotherapy. The phase I part included 6 patients with untreated locally-advanced or mTNBC to determine the safety and recommended phase II dose of the anti-CD73 antibody oleclumab in combination with the anti-PD-L1 durvalumab and 12 cycles of weekly carboplatin and paclitaxel. In the phase II part, 127 women were randomized 1:1 to receive chemo-immunotherapy, with (arm A) or without (arm B) oleclumab. The primary endpoint was the clinical benefit rate at week 24, defined as stable disease, partial or complete response per RECIST v1.1. Secondary endpoints included objective response rate, duration of response, survival outcomes (progression-free survival and overall survival), and safety. The trial did not meet its primary endpoint, as the 24-week clinical benefit rate was not significantly improved by adding oleclumab (43% vs. 44%, p = 0.61). Exploratory median progression-free survival was 5.9 months in arm A as compared to 7.0 months in arm B (p = 0.90). The safety profile was manageable in both arms.

Most random gene expression signatures are significantly associated with breast cancer outcome.

Bridging the gap between animal or in vitro models and human disease is essential in medical research. Researchers often suggest that a biological mechanism is relevant to human cancer from the statistical association of a gene expression marker (a signature) of this mechanism, that was discovered in an experimental system, with disease outcome in humans. We examined this argument for breast cancer. Surprisingly, we found that gene expression signatures-unrelated to cancer-of the effect of postprandial laughter, of mice social defeat and of skin fibroblast localization were all significantly associated with breast cancer outcome. We next compared 47 published breast cancer outcome signatures to signatures made of random genes. Twenty-eight of them (60%) were not significantly better outcome predictors than random signatures of identical size and 11 (23%) were worst predictors than the median random signature. More than 90% of random signatures >100 genes were significant outcome predictors. We next derived a metagene, called meta-PCNA, by selecting the 1% genes most positively correlated with proliferation marker PCNA in a compendium of normal tissues expression. Adjusting breast cancer expression data for meta-PCNA abrogated almost entirely the outcome association of published and random signatures. We also found that, in the absence of adjustment, the hazard ratio of outcome association of a signature strongly correlated with meta-PCNA (R(2) = 0.9). This relation also applied to single-gene expression markers. Moreover, >50% of the breast cancer transcriptome was correlated with meta-PCNA. A corollary was that purging cell cycle genes out of a signature failed to rule out the confounding effect of proliferation. Hence, it is questionable to suggest that a mechanism is relevant to human breast cancer from the finding that a gene expression marker for this mechanism predicts human breast cancer outcome, because most markers do. The methods we present help to overcome this problem.

A statistical approach to central monitoring of data quality in clinical trials.

BACKGROUND: Classical monitoring approaches rely on extensive on-site visits and source data verification. These activities are associated with high cost and a limited contribution to data quality. Central statistical monitoring is of particular interest to address these shortcomings. PURPOSE: This article outlines the principles of central statistical monitoring and the challenges of implementing it in actual trials. METHODS: A statistical approach to central monitoring is based on a large number of statistical tests performed on all variables collected in the database, in order to identify centers that differ from the others. The tests generate a high-dimensional matrix of p-values, which can be analyzed by statistical methods and bioinformatic tools to identify extreme centers. RESULTS: Results from actual trials are provided to illustrate typical findings that can be expected from a central statistical monitoring approach, which detects abnormal patterns that were not (or could not have been) detected by on-site monitoring. LIMITATIONS: Central statistical monitoring can only address problems present in the data. Important aspects of trial conduct such as a lack of informed consent documentation, for instance, require other approaches. The results provided here are empirical examples from a limited number of studies. CONCLUSION: Central statistical monitoring can both optimize on-site monitoring and improve data quality and as such provides a cost-effective way of meeting regulatory requirements for clinical trials.

Interrogating breast cancer heterogeneity using single and pooled circulating tumor cell analysis.

Single cell technologies allow the interrogation of tumor heterogeneity, providing insights into tumor evolution and treatment resistance. To better understand whether circulating tumor cells (CTCs) could complement metastatic biopsies for tumor genomic profiling, we characterized 11 single CTCs and 10 pooled CTC samples at the mutational and copy number aberration (CNA) levels, and compared these results with matched synchronous tumor biopsies from 3 metastatic breast cancer patients with triple-negative (TNBC), HER2-positive and estrogen receptor-positive (ER+) tumors. Similar CNA profiles and the same patient-specific driver mutations were found in bulk tissue and CTCs for the HER2-positive and TNBC tumors, whereas different CNA profiles and driver mutations were identified for the ER+ tumor, which presented two distinct clones in CTCs defined by mutations in ESR1 Y537N and TP53, respectively. Furthermore, de novo mutational signatures derived from CTCs described patient-specific biological processes. These data suggest that tumor tissue and CTCs provide complementary clinically relevant information to map tumor heterogeneity and tumor evolution.

Circulating Tumor DNA After Neoadjuvant Chemotherapy in Breast Cancer Is Associated With Disease Relapse.

PURPOSE: Detection of circulating tumor DNA (ctDNA) after neoadjuvant chemotherapy in patients with early-stage breast cancer may allow for early detection of relapse. In this study, we analyzed ctDNA using a personalized, tumor-informed multiplex polymerase chain reaction-based next-generation sequencing assay. METHODS: Plasma samples (n = 157) from 44 patients were collected before neoadjuvant therapy (baseline), after neoadjuvant therapy and before surgery (presurgery), and serially postsurgery including a last follow-up sample. The primary end point was event-free survival (EFS) analyzed using Cox regression models. RESULTS: Thirty-eight (86%), 41 (93%), and 38 (86%) patients had baseline, presurgical, and last follow-up samples, respectively. Twenty patients had hormone receptor-positive/human epidermal growth factor receptor 2-negative, 13 had triple-negative breast cancer, and 11 had human epidermal growth factor receptor 2-positive disease. Baseline ctDNA detection was observed in 22/38 (58%) patients and was significantly associated with Ki67 > 20% (P = .036) and MYC copy-number gain (P = .0025, false discovery rate = 0.036). ctDNA detection at presurgery and at last follow-up was observed in 2/41 (5%) and 2/38 (5%) patients, respectively. Eight relapses (seven distant and one local) were noted (median follow-up 3.03 years [range, 0.39-5.85 years]). After adjusting for pathologic complete response (pCR), ctDNA detection at presurgery and at last follow-up was associated with shorter EFS (hazard ratio [HR], 53; 95% CI, 4.5 to 624; P < .01, and HR, 31; 95% CI, 2.7 to 352; P < .01, respectively). Association between baseline detection and EFS was not observed (HR, 1.4; 95% CI, 0.3 to 5.9; P = .67). CONCLUSION: The presence of ctDNA after neoadjuvant chemotherapy is associated with relapse in early-stage breast cancer, supporting interventional trials for testing the clinical utility of ctDNA monitoring in this setting.

Timing evolution of lobular breast cancer through phylogenetic analysis.

BACKGROUND: Late distant recurrence is a challenge for the treatment of invasive lobular carcinoma (ILC) of the breast. Despite in-depth characterisation of primary ILC, the molecular landscape of metastatic ILC is still only partially understood. METHODS: We retrospectively identified 38 ILC patients from the tissue banks of six European institutions. DNA extracted from patient matched primary and metastatic FFPE tissue blocks was whole genome sequenced to compute somatic copy number aberrations. This, in turn, was used to infer the evolutionary history of these patients. FINDINGS: The data show different metastatic seeding patterns, with both an early and late divergence of the metastatic lineage observed in ILC. Additionally, cascading dissemination from a metastatic precursor was a dominant rule. Alterations in key cancer driver genes, such as TP53 or CCND1, were acquired early while additional aberrations were present only in the metastatic branch. In about 30% of the patients, the metastatic lineage harboured less aberrations than the primary tumour suggesting a period of tumour dormancy or prolonged adaptation at the distant site. This phenomenon was mostly observed in tumours from de novo metastatic patients. INTERPRETATION: Our results provide insights into ILC evolution and offer potential paths for optimised ILC care. FUNDING: This work has received financial support from Les Amis de l'Institut Bordet, MEDIC, the Breast Cancer Research Foundation (BCRF) and the Belgian Fonds National de la Recherche Scientifique (F.R.S-FNRS).

Cancer cells resist antibody-mediated destruction by neutrophils through activation of the exocyst complex.

BACKGROUND: Neutrophils kill antibody-opsonized tumor cells using trogocytosis, a unique mechanism of destruction of the target plasma. This previously unknown cytotoxic process of neutrophils is dependent on antibody opsonization, Fcγ receptors and CD11b/CD18 integrins. Here, we demonstrate that tumor cells can escape neutrophil-mediated cytotoxicity by calcium (Ca2+)-dependent and exocyst complex-dependent plasma membrane repair. METHODS: We knocked down EXOC7 or EXOC4, two exocyst components, to evaluate their involvement in tumor cell membrane repair after neutrophil-induced trogocytosis. We used live cell microscopy and flow cytometry for visualization of the host and tumor cell interaction and tumor cell membrane repair. Last, we reported the mRNA levels of exocyst in breast cancer tumors in correlation to the response in trastuzumab-treated patients. RESULTS: We found that tumor cells can evade neutrophil antibody-dependent cellular cytotoxicity (ADCC) by Ca2+-dependent cell membrane repair, a process induced upon neutrophil trogocytosis. Absence of exocyst components EXOC7 or EXOC4 rendered tumor cells vulnerable to neutrophil-mediated ADCC (but not natural killer cell-mediated killing), while neutrophil trogocytosis remained unaltered. Finally, mRNA levels of exocyst components in trastuzumab-treated patients were inversely correlated to complete response to therapy. CONCLUSIONS: Our results support that neutrophil attack towards antibody-opsonized cancer cells by trogocytosis induces an active repair process by the exocyst complex in vitro. Our findings provide insight to the possible contribution of neutrophils in current antibody therapies and the tolerance mechanism of tumor cells and support further studies for potential use of the exocyst components as clinical biomarkers.

Ontogeny and Vulnerabilities of Drug-Tolerant Persisters in HER2+ Breast Cancer.

Resistance to targeted therapies is an important clinical problem in HER2-positive (HER2+) breast cancer. "Drug-tolerant persisters" (DTP), a subpopulation of cancer cells that survive via reversible, nongenetic mechanisms, are implicated in resistance to tyrosine kinase inhibitors (TKI) in other malignancies, but DTPs following HER2 TKI exposure have not been well characterized. We found that HER2 TKIs evoke DTPs with a luminal-like or a mesenchymal-like transcriptome. Lentiviral barcoding/single-cell RNA sequencing reveals that HER2+ breast cancer cells cycle stochastically through a "pre-DTP" state, characterized by a G0-like expression signature and enriched for diapause and/or senescence genes. Trajectory analysis/cell sorting shows that pre-DTPs preferentially yield DTPs upon HER2 TKI exposure. Cells with similar transcriptomes are present in HER2+ breast tumors and are associated with poor TKI response. Finally, biochemical experiments indicate that luminal-like DTPs survive via estrogen receptor-dependent induction of SGK3, leading to rewiring of the PI3K/AKT/mTORC1 pathway to enable AKT-independent mTORC1 activation. SIGNIFICANCE: DTPs are implicated in resistance to anticancer therapies, but their ontogeny and vulnerabilities remain unclear. We find that HER2 TKI-DTPs emerge from stochastically arising primed cells ("pre-DTPs") that engage either of two distinct transcriptional programs upon TKI exposure. Our results provide new insights into DTP ontogeny and potential therapeutic vulnerabilities. This article is highlighted in the In This Issue feature, p. 873.

FDG positron emission tomography imaging and ctDNA detection as an early dynamic biomarker of everolimus efficacy in advanced luminal breast cancer.

Biomarkers to identify patients without benefit from adding everolimus to endocrine treatment in metastatic breast cancer (MBC) are needed. We report the results of the Pearl trial conducted in five Belgian centers assessing 18F-FDG-PET/CT non-response (n = 45) and ctDNA detection (n = 46) after 14 days of exemestane-everolimus (EXE-EVE) to identify MBC patients who will not benefit. The metabolic non-response rate was 66.6%. Median PFS in non-responding patients (using as cut-off 25% for SUVmax decrease) was 3.1 months compared to 6.0 months in those showing response (HR: 0.77, 95% CI: 0.40-1.50, p = 0.44). The difference was significant when using a "post-hoc" cut-off of 15% (PFS 2.2 months vs 6.4 months). ctDNA detection at D14 was associated with PFS: 2.1 months vs 5.0 months (HR-2.5, 95% CI: 1.3-5.0, p = 0.012). Detection of ctDNA and/or the absence of 18F-FDG-PET/CT response after 14 days of EXE-EVE identifies patients with a low probability of benefiting from treatment. Independent validation is needed.

Copy Number Aberration Analysis to Predict Response to Neoadjuvant Anti-HER2 Therapy: Results from the NeoALTTO Phase III Clinical Trial.

PURPOSE: The heterogeneity of response to anti-HER2 agents represents a major challenge in patients with HER2-positive breast cancer. To better understand the sensitivity and resistance to trastuzumab and lapatinib, we investigated the role of copy number aberrations (CNA) in predicting pathologic complete response (pCR) and survival outcomes in the NeoALTTO trial. EXPERIMENTAL DESIGN: The neoadjuvant phase III NeoALTTO trial enrolled 455 patients with HER2-positive early-stage breast cancer. DNA samples from 269 patients were assessed for genome-wide copy number profiling. Recurrent CNAs were found with GISTIC2.0. RESULTS: CNA estimates were obtained for 184 patients included in NeoALTTO. Among those, matched transcriptome and whole-exome data were available for 154 and 181 patients, respectively. A significant association between gene copy number and pCR was demonstrated for ERBB2 amplification. Nevertheless, ERBB2 amplification ceased to be predictive once ERBB2 expression level was considered. GISTIC2.0 analysis revealed 159 recurrent CNA regions. Lower copy number levels of the 6q23-24 locus predicted absence of pCR in the whole cohort and in the estrogen receptor-positive subgroup. 6q23-24 deletion was significantly more frequent in TP53 wild-type (WT) compared with TP53-mutated, resulting in copy number levels significantly associated with lack of pCR only in the TP53 WT subgroup. Interestingly, a gene-ontology analysis highlighted several immune processes correlated to 6q23-24 copy number. CONCLUSIONS: Our analysis identified ERBB2 copy number as well as 6q23-24 CNAs as predictors of response to anti-HER2-based treatment. ERBB2 expression outperformed ERBB2 amplification. The complexity of the 6q23-24 region warrants further investigation.