B Cells and T Follicular Helper Cells Mediate Response to Checkpoint Inhibitors in High Mutation Burden Mouse Models of Breast Cancer.

This study identifies mechanisms mediating responses to immune checkpoint inhibitors using mouse models of triple-negative breast cancer. By creating new mammary tumor models, we find that tumor mutation burden and specific immune cells are associated with response. Further, we developed a rich resource of single-cell RNA-seq and bulk mRNA-seq data of immunotherapy-treated and non-treated tumors from sensitive and resistant murine models. Using this, we uncover that immune checkpoint therapy induces T follicular helper cell activation of B cells to facilitate the anti-tumor response in these models. We also show that B cell activation of T cells and the generation of antibody are key to immunotherapy response and propose a new biomarker for immune checkpoint therapy. In total, this work presents resources of new preclinical models of breast cancer with large mRNA-seq and single-cell RNA-seq datasets annotated for sensitivity to therapy and uncovers new components of response to immune checkpoint inhibitors.

Comprehensive Molecular Portraits of Invasive Lobular Breast Cancer.

Invasive lobular carcinoma (ILC) is the second most prevalent histologic subtype of invasive breast cancer. Here, we comprehensively profiled 817 breast tumors, including 127 ILC, 490 ductal (IDC), and 88 mixed IDC/ILC. Besides E-cadherin loss, the best known ILC genetic hallmark, we identified mutations targeting PTEN, TBX3, and FOXA1 as ILC enriched features. PTEN loss associated with increased AKT phosphorylation, which was highest in ILC among all breast cancer subtypes. Spatially clustered FOXA1 mutations correlated with increased FOXA1 expression and activity. Conversely, GATA3 mutations and high expression characterized luminal A IDC, suggesting differential modulation of ER activity in ILC and IDC. Proliferation and immune-related signatures determined three ILC transcriptional subtypes associated with survival differences. Mixed IDC/ILC cases were molecularly classified as ILC-like and IDC-like revealing no true hybrid features. This multidimensional molecular atlas sheds new light on the genetic bases of ILC and provides potential clinical options.

MRE11 liberates cGAS from nucleosome sequestration during tumorigenesis.

Oncogene-induced replication stress generates endogenous DNA damage that activates cGAS-STING-mediated signalling and tumour suppression1-3. However, the precise mechanism of cGAS activation by endogenous DNA damage remains enigmatic, particularly given that high-affinity histone acidic patch (AP) binding constitutively inhibits cGAS by sterically hindering its activation by double-stranded DNA (dsDNA)4-10. Here we report that the DNA double-strand break sensor MRE11 suppresses mammary tumorigenesis through a pivotal role in regulating cGAS activation. We demonstrate that binding of the MRE11-RAD50-NBN complex to nucleosome fragments is necessary to displace cGAS from acidic-patch-mediated sequestration, which enables its mobilization and activation by dsDNA. MRE11 is therefore essential for cGAS activation in response to oncogenic stress, cytosolic dsDNA and ionizing radiation. Furthermore, MRE11-dependent cGAS activation promotes ZBP1-RIPK3-MLKL-mediated necroptosis, which is essential to suppress oncogenic proliferation and breast tumorigenesis. Notably, downregulation of ZBP1 in human triple-negative breast cancer is associated with increased genome instability, immune suppression and poor patient prognosis. These findings establish MRE11 as a crucial mediator that links DNA damage and cGAS activation, resulting in tumour suppression through ZBP1-dependent necroptosis.

Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin.

Recent genomic analyses of pathologically defined tumor types identify "within-a-tissue" disease subtypes. However, the extent to which genomic signatures are shared across tissues is still unclear. We performed an integrative analysis using five genome-wide platforms and one proteomic platform on 3,527 specimens from 12 cancer types, revealing a unified classification into 11 major subtypes. Five subtypes were nearly identical to their tissue-of-origin counterparts, but several distinct cancer types were found to converge into common subtypes. Lung squamous, head and neck, and a subset of bladder cancers coalesced into one subtype typified by TP53 alterations, TP63 amplifications, and high expression of immune and proliferation pathway genes. Of note, bladder cancers split into three pan-cancer subtypes. The multiplatform classification, while correlated with tissue-of-origin, provides independent information for predicting clinical outcomes. All data sets are available for data-mining from a unified resource to support further biological discoveries and insights into novel therapeutic strategies.

A multi-omic single-cell landscape of human gynecologic malignancies.

Deconvolution of regulatory mechanisms that drive transcriptional programs in cancer cells is key to understanding tumor biology. Herein, we present matched transcriptome (scRNA-seq) and chromatin accessibility (scATAC-seq) profiles at single-cell resolution from human ovarian and endometrial tumors processed immediately following surgical resection. This dataset reveals the complex cellular heterogeneity of these tumors and enabled us to quantitatively link variation in chromatin accessibility to gene expression. We show that malignant cells acquire previously unannotated regulatory elements to drive hallmark cancer pathways. Moreover, malignant cells from within the same patients show substantial variation in chromatin accessibility linked to transcriptional output, highlighting the importance of intratumoral heterogeneity. Finally, we infer the malignant cell type-specific activity of transcription factors. By defining the regulatory logic of cancer cells, this work reveals an important reliance on oncogenic regulatory elements and highlights the ability of matched scRNA-seq/scATAC-seq to uncover clinically relevant mechanisms of tumorigenesis in gynecologic cancers.

The somatic genomic landscape of glioblastoma.

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

Dynamic reprogramming of the kinome in response to targeted MEK inhibition in triple-negative breast cancer.

Kinase inhibitors have limited success in cancer treatment because tumors circumvent their action. Using a quantitative proteomics approach, we assessed kinome activity in response to MEK inhibition in triple-negative breast cancer (TNBC) cells and genetically engineered mice (GEMMs). MEK inhibition caused acute ERK activity loss, resulting in rapid c-Myc degradation that induced expression and activation of several receptor tyrosine kinases (RTKs). RNAi knockdown of ERK or c-Myc mimicked RTK induction by MEK inhibitors, and prevention of proteasomal c-Myc degradation blocked kinome reprogramming. MEK inhibitor-induced RTK stimulation overcame MEK2 inhibition, but not MEK1 inhibition, reactivating ERK and producing drug resistance. The C3Tag GEMM for TNBC similarly induced RTKs in response to MEK inhibition. The inhibitor-induced RTK profile suggested a kinase inhibitor combination therapy that produced GEMM tumor apoptosis and regression where single agents were ineffective. This approach defines mechanisms of drug resistance, allowing rational design of combination therapies for cancer.

Research autopsy programmes in oncology: shared experience from 14 centres across the world.

While there is a great clinical need to understand the biology of metastatic cancer in order to treat it more effectively, research is hampered by limited sample availability. Research autopsy programmes can crucially advance the field through synchronous, extensive, and high-volume sample collection. However, it remains an underused strategy in translational research. Via an extensive questionnaire, we collected information on the study design, enrolment strategy, study conduct, sample and data management, and challenges and opportunities of research autopsy programmes in oncology worldwide. Fourteen programmes participated in this study. Eight programmes operated 24 h/7 days, resulting in a lower median postmortem interval (time between death and start of the autopsy, 4 h) compared with those operating during working hours (9 h). Most programmes (n = 10) succeeded in collecting all samples within a median of 12 h after death. A large number of tumour sites were sampled during each autopsy (median 15.5 per patient). The median number of samples collected per patient was 58, including different processing methods for tumour samples but also non-tumour tissues and liquid biopsies. Unique biological insights derived from these samples included metastatic progression, treatment resistance, disease heterogeneity, tumour dormancy, interactions with the tumour micro-environment, and tumour representation in liquid biopsies. Tumour patient-derived xenograft (PDX) or organoid (PDO) models were additionally established, allowing for drug discovery and treatment sensitivity assays. Apart from the opportunities and achievements, we also present the challenges related with postmortem sample collections and strategies to overcome them, based on the shared experience of these 14 programmes. Through this work, we hope to increase the transparency of postmortem tissue donation, to encourage and aid the creation of new programmes, and to foster collaborations on these unique sample collections. © 2024 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

BIRC5 expression by race, age and clinical factors in breast cancer patients.

PURPOSE: Survivin/BIRC5 is a proliferation marker that is associated with poor prognosis in breast cancer and an attractive therapeutic target. However, BIRC5 has not been well studied among racially diverse populations where aggressive breast cancers are prevalent. EXPERIMENTAL DESIGN: We studied BIRC5 expression in association with clinical and demographic variables and as a predictor of recurrence in 2174 participants in the Carolina Breast Cancer Study (CBCS), a population-based study that oversampled Black (n = 1113) and younger (< 50 years; n = 1137) participants with breast cancer. For comparison, similar analyses were conducted in The Cancer Genome Atlas [TCGA N = 1094, Black (n = 183), younger (n = 295)]. BIRC5 was evaluated as a continuous and categorical variable (highest quartile vs. lower three quartiles). RESULTS: Univariate, continuous BIRC5 expression was higher in breast tumors from Black women relative to non-Black women in both estrogen receptor (ER)-positive and ER-negative tumors and in analyses stratified by stage (i.e., within Stage I, Stage II, and Stage III/IV tumors). Within CBCS and TCGA, BIRC5-high was associated with young age (< 50 years) and Black race, as well as hormone receptor-negative tumors, non-Luminal A PAM50 subtypes, advanced stage, and larger tumors (> 2 cm). Relative to BIRC5-low, BIRC5-high tumors were associated with poor 5-year recurrence-free survival (RFS) among ER-positive tumors, both in unadjusted models [HR (95% CI): 2.7 (1.6, 4.6)] and after adjustment for age and stage [Adjusted HR (95% CI): 1.87 (1.07, 3.25)]. However, this relationship was not observed among ER-negative tumors [Crude HR (95% CI): 0.7 (0.39, 1.2); Adjusted HR (95% CI): 0.67 (0.37, 1.2)]. CONCLUSION: Black and younger women with breast cancer have a higher burden of BIRC5-high tumors than older and non-Black women. Emerging anti-survivin treatment strategies may be an important future direction for equitable breast cancer outcomes.

OptimICE-RD: sacituzumab govitecan + pembrolizumab vs pembrolizumab (± capecitabine) for residual triple-negative breast cancer.

Patients with early-stage triple-negative breast cancer (TNBC) with residual invasive disease after neoadjuvant therapy have a high risk of recurrence even with neoadjuvant and adjuvant treatment with pembrolizumab. Sacituzumab govitecan, a Trop-2-directed antibody-drug conjugate with a topoisomerase I inhibitor payload, improved progression-free survival (PFS) and overall survival (OS) versus chemotherapy in patients with pre-treated metastatic TNBC. Moreover, preclinical data suggest that topoisomerase I inhibitors may enhance the effects of immune checkpoint inhibitors through activation of the cGAS-STING pathway. Here we describe the international randomized phase III AFT-65/ASCENT-05/OptimICE-RD trial, which evaluates the efficacy and safety of sacituzumab govitecan plus pembrolizumab versus treatment of physician's choice (pembrolizumab ± capecitabine) among patients with early-stage TNBC with residual invasive disease after neoadjuvant therapy.Clinical Trial Registration: NCT05633654 (ClinicalTrials.gov)Other Study ID Number(s): Gilead Study ID: GS-US-595-6184Registration date: 1 December 2022Study start date: 12 December 2022Recruitment status: Recruiting.

AFT-65/ASCENT-05/OptimICE-RD is an ongoing clinical trial that is testing a new treatment combination for patients with stage II or III triple-negative breast cancer (TNBC). Stage II­III means the cancer is confined to the breast and/or nearby lymph nodes and can be surgically removed. However, there remains a risk that the cancer could recur after surgery. To reduce this risk, patients with stage II­III TNBC receive anti-cancer medication before and after surgery. For some patients, receipt of anti-cancer medication before surgery produces a pathologic complete response (pCR), meaning there is no observable cancer left behind at surgery. Patients with a pCR have a lower risk of recurrence than patients with residual disease.The AFT-65/ASCENT-05/OptimICE-RD trial includes people with stage II-III TNBC who have residual cancer after completing their course of pre-surgery anti-cancer medication. All participants have any remaining cancer in their breast and/or lymph nodes removed surgically, after which they are randomly assigned to receive one of two treatments. The experimental therapy consists of pembrolizumab along with a medication called sacituzumab govitecan, which kills cancer cells directly and may strengthen the anti-cancer immune response. Pembrolizumab strengthens the anti-cancer immune response, so the hypothesis of this trial is that the two medications will be more effective together. The control therapy consists of pembrolizumab, alone or in combination with a chemotherapy medication called capecitabine, which is the current standard of care. To study the effectiveness of each treatment, the researchers are following up with all participants to learn if and when their breast cancer returns.

Asparagine bioavailability governs metastasis in a model of breast cancer.

Using a functional model of breast cancer heterogeneity, we previously showed that clonal sub-populations proficient at generating circulating tumour cells were not all equally capable of forming metastases at secondary sites. A combination of differential expression and focused in vitro and in vivo RNA interference screens revealed candidate drivers of metastasis that discriminated metastatic clones. Among these, asparagine synthetase expression in a patient's primary tumour was most strongly correlated with later metastatic relapse. Here we show that asparagine bioavailability strongly influences metastatic potential. Limiting asparagine by knockdown of asparagine synthetase, treatment with l-asparaginase, or dietary asparagine restriction reduces metastasis without affecting growth of the primary tumour, whereas increased dietary asparagine or enforced asparagine synthetase expression promotes metastatic progression. Altering asparagine availability in vitro strongly influences invasive potential, which is correlated with an effect on proteins that promote the epithelial-to-mesenchymal transition. This provides at least one potential mechanism for how the bioavailability of a single amino acid could regulate metastatic progression.

Erratum: Asparagine bioavailability governs metastasis in a model of breast cancer.

This corrects the article DOI: 10.1038/nature25465.

SCDC: bulk gene expression deconvolution by multiple single-cell RNA sequencing references.

Recent advances in single-cell RNA sequencing (scRNA-seq) enable characterization of transcriptomic profiles with single-cell resolution and circumvent averaging artifacts associated with traditional bulk RNA sequencing (RNA-seq) data. Here, we propose SCDC, a deconvolution method for bulk RNA-seq that leverages cell-type specific gene expression profiles from multiple scRNA-seq reference datasets. SCDC adopts an ENSEMBLE method to integrate deconvolution results from different scRNA-seq datasets that are produced in different laboratories and at different times, implicitly addressing the problem of batch-effect confounding. SCDC is benchmarked against existing methods using both in silico generated pseudo-bulk samples and experimentally mixed cell lines, whose known cell-type compositions serve as ground truths. We show that SCDC outperforms existing methods with improved accuracy of cell-type decomposition under both settings. To illustrate how the ENSEMBLE framework performs in complex tissues under different scenarios, we further apply our method to a human pancreatic islet dataset and a mouse mammary gland dataset. SCDC returns results that are more consistent with experimental designs and that reproduce more significant associations between cell-type proportions and measured phenotypes.

Anti-PD-1 Checkpoint Therapy Can Promote the Function and Survival of Regulatory T Cells.

We have previously shown in a model of claudin-low breast cancer that regulatory T cells (Tregs) are increased in the tumor microenvironment (TME) and express high levels of PD-1. In mouse models and patients with triple-negative breast cancer, it is postulated that one cause for the lack of activity of anti-PD-1 therapy is the activation of PD-1-expressing Tregs in the TME. We hypothesized that the expression of PD-1 on Tregs would lead to enhanced suppressive function of Tregs and worsen antitumor immunity during PD-1 blockade. To evaluate this, we isolated Tregs from claudin-low tumors and functionally evaluated them ex vivo. We compared transcriptional profiles of Tregs isolated from tumor-bearing mice with or without anti-PD-1 therapy using RNA sequencing. We found several genes associated with survival and proliferation pathways; for example, Jun, Fos, and Bcl2 were significantly upregulated in Tregs exposed to anti-PD-1 treatment. Based on these data, we hypothesized that anti-PD-1 treatment on Tregs results in a prosurvival phenotype. Indeed, Tregs exposed to PD-1 blockade had significantly higher levels of Bcl-2 expression, and this led to increased protection from glucocorticoid-induced apoptosis. In addition, we found in vitro and in vivo that Tregs in the presence of anti-PD-1 proliferated more than control Tregs PD-1 blockade significantly increased the suppressive activity of Tregs at biologically relevant Treg/Tnaive cell ratios. Altogether, we show that this immunotherapy blockade increases proliferation, protection from apoptosis, and suppressive capabilities of Tregs, thus leading to enhanced immunosuppression in the TME.

Clinical subtype, treatment response, and survival in De Novo and recurrent metastatic breast cancer.

PURPOSE: This study evaluated whether patients with de novo metastatic breast cancer (MBC) have superior outcomes compared to those with recurrent MBC in a contemporary treatment era and examined factors related to outcome differentials. METHODS: Using an institutional database, we examined patient and tumor characteristics, treatment response, and outcome among 232 patients with de novo and 612 patients with recurrent MBC diagnosed between 2011 and 2017. RESULTS: De novo MBC had 9-month (m) longer overall survival (OS) than recurrent MBC (36.4 vs 27.4 m, p < 0.001). Contributions to this difference included nearly twofold more HER2-positive (29.3% vs 15.2%) and significantly fewer triple-negative breast cancers (20.3% vs 32.4%, both p < 0.001) in de novo compared with recurrent MBC cohorts. Stratified by clinical subtype, progression-free survival (PFS) on first-line therapy was significantly longer in de novo MBC in all but the triple-negative subtype, 25.5 vs 11.6 m (p < 0.001) among 390 patients with hormone receptor-positive, HER2-negative, 11.4 vs 5.4 m (p = 0.002) among 142 patients with HER2-positive, and 4.0 vs 3.0 m (p = 0.121) among 162 with triple-negative MBC. In multivariable analysis, de novo status remained independently associated with improved OS (hazard ratio 0.63, 95% CI 0.49-0.80), regardless of subtype and other features. CONCLUSION: Patients with de novo MBC have better outcomes than those with recurrent MBC. Differences in clinical subtype and response to therapy in the metastatic setting contribute to, but do not fully explain, this difference. Longer PFS to first-line therapy in de novo MBC suggests biologic differences compared to recurrent MBC, which may be intrinsic or due to acquired resistance from treatment for prior localized breast cancer in recurrent disease.

Proteogenomics connects somatic mutations to signalling in breast cancer.

Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.

PDGFRß is an essential therapeutic target for BRCA1-deficient mammary tumors.

BACKGROUND: Basal-like breast cancers (BLBCs) are a leading cause of cancer death due to their capacity to metastasize and lack of effective therapies. More than half of BLBCs have a dysfunctional BRCA1. Although most BRCA1-deficient cancers respond to DNA-damaging agents, resistance and tumor recurrence remain a challenge to survival outcomes for BLBC patients. Additional therapies targeting the pathways aberrantly activated by BRCA1 deficiency are urgently needed. METHODS: Most BRCA1-deficient BLBCs carry a dysfunctional INK4-RB pathway. Thus, we created genetically engineered mice with Brca1 loss and deletion of p16INK4A, or separately p18INK4C, to model the deficient INK4-RB signaling in human BLBC. By using these mutant mice and human BRCA1-deficient and proficient breast cancer tissues and cells, we tested if there exists a druggable target in BRCA1-deficient breast cancers. RESULTS: Heterozygous germline or epithelium-specific deletion of Brca1 in p18INK4C- or p16INK4A-deficient mice activated Pdgfrß signaling, induced epithelial-to-mesenchymal transition, and led to BLBCs. Confirming this role, targeted deletion of Pdgfrß in Brca1-deficient tumor cells promoted cell death, induced mesenchymal-to-epithelial transition, and suppressed tumorigenesis. Importantly, we also found that pharmaceutical inhibition of Pdgfrß and its downstream target Pkcα suppressed Brca1-deficient tumor initiation and progression and effectively killed BRCA1-deficient cancer cells. CONCLUSIONS: Our work offers the first genetic and biochemical evidence that PDGFRß-PKCα signaling is repressed by BRCA1, which establishes PDGFRß-PKCα signaling as a therapeutic target for BRCA1-deficient breast cancers.

Clinical and genomic assessment of PD-L1 SP142 expression in triple-negative breast cancer.

PURPOSE: The SP142 PD-L1 assay is a companion diagnostic for atezolizumab in metastatic triple-negative breast cancer (TNBC). We strove to understand the biological, genomic, and clinical characteristics associated with SP142 PD-L1 positivity in TNBC patients. METHODS: Using 149 TNBC formalin-fixed paraffin-embedded tumor samples, tissue microarray (TMA) and gene expression microarrays were performed in parallel. The VENTANA SP142 assay was used to identify PD-L1 expression from TMA slides. We next generated a gene signature reflective of SP142 status and evaluated signature distribution according to TNBCtype and PAM50 subtypes. A SP142 gene expression signature was identified and was biologically and clinically evaluated on the TNBCs of TCGA, other cohorts, and on other malignancies treated with immune checkpoint inhibitors (ICI). RESULTS: Using SP142, 28.9% of samples were PD-L1 protein positive. The SP142 PD-L1-positive TNBC had higher CD8+ T cell percentage, stromal tumor-infiltrating lymphocyte levels, and higher rate of the immunomodulatory TNBCtype compared to PD-L1-negative samples. The recurrence-free survival was prolonged in PD-L1-positive TNBC. The SP142-guided gene expression signature consisted of 94 immune-related genes. The SP142 signature was associated with a higher pathologic complete response rate and better survival in multiple TNBC cohorts. In the TNBC of TCGA, this signature was correlated with lymphocyte-infiltrating signature scores, but not with tumor mutational burden or total neoantigen count. In other malignancies treated with ICIs, the SP142 genomic signature was associated with improved response and survival. CONCLUSIONS: We provide multi-faceted evidence that SP142 PDL1-positive TNBC have immuno-genomic features characterized as highly lymphocyte-infiltrated and a relatively favorable survival.

Serial single-cell profiling analysis of metastatic TNBC during Nab-paclitaxel and pembrolizumab treatment.

PURPOSE: Immunotherapy has recently been shown to improve outcomes for advanced PD-L1-positive triple-negative breast cancer (TNBC) in the Impassion130 trial, leading to FDA approval of the first immune checkpoint inhibitor in combination with taxane chemotherapy. To further develop predictive biomarkers and improve therapeutic efficacy of the combination, interrogation of the tumor immune microenvironment before therapy as well as during each component of treatment is crucial. Here we use single-cell RNA sequencing (scRNA-seq) on tumor biopsies to assess immune cell changes from two patients with advanced TNBC treated in a prospective trial at predefined serial time points, before treatment, on taxane chemotherapy and on chemo-immunotherapy. METHODS: Both patients (one responder and one progressor) received the trial therapy, in cycle 1 nab-paclitaxel given as single agent, in cycle 2 nab-paclitaxel in combination with pembrolizumab. Tumor core biopsies were obtained at baseline, 3 weeks (after cycle 1, chemotherapy alone) and 6 weeks (after cycle 2, chemo-immunotherapy). Single-cell RNA sequencing (scRNA-seq) of both cancer cells and infiltrating immune cells isolated were performed from fresh tumor core biopsy specimens by 10 × chromium sequencing. RESULTS: ScRNA-seq analysis showed significant baseline heterogeneity of tumor-infiltrating immune cell populations between the two patients as well as modulation of the tumor microenvironment by chemotherapy and immunotherapy. In the responding patient there was a population of PD-1high-expressing T cells which significantly decreased after nab-paclitaxel plus pembrolizumab treatment as well as a presence of tissue-resident memory T cells (TRM). In contrast, tumors from the patient with rapid disease progression showed a prevalent and persistent myeloid compartment. CONCLUSIONS: Our study provides a deep cellular analysis of on-treatment changes during chemo-immunotherapy for advanced TNBC, demonstrating not only feasibility of single-cell analyses on serial tumor biopsies but also the heterogeneity of TNBC and differences in on-treatment changes in responder versus progressor.

Receiver operating characteristic curves and confidence bands for support vector machines.

Many problems that appear in biomedical decision-making, such as diagnosing disease and predicting response to treatment, can be expressed as binary classification problems. The support vector machine (SVM) is a popular classification technique that is robust to model misspecification and effectively handles high-dimensional data. The relative costs of false positives and false negatives can vary across application domains. The receiving operating characteristic (ROC) curve provides a visual representation of the trade-off between these two types of errors. Because the SVM does not produce a predicted probability, an ROC curve cannot be constructed in the traditional way of thresholding a predicted probability. However, a sequence of weighted SVMs can be used to construct an ROC curve. Although ROC curves constructed using weighted SVMs have great potential for allowing ROC curves analyses that cannot be done by thresholding predicted probabilities, their theoretical properties have heretofore been underdeveloped. We propose a method for constructing confidence bands for the SVM ROC curve and provide the theoretical justification for the SVM ROC curve by showing that the risk function of the estimated decision rule is uniformly consistent across the weight parameter. We demonstrate the proposed confidence band method using simulation studies. We present a predictive model for treatment response in breast cancer as an illustrative example.