Longitudinal molecular profiling elucidates immunometabolism dynamics in breast cancer.

Although metabolic reprogramming within tumor cells and tumor microenvironment (TME) is well described in breast cancer, little is known about how the interplay of immune state and cancer metabolism evolves during treatment. Here, we characterize the immunometabolic profiles of tumor tissue samples longitudinally collected from individuals with breast cancer before, during and after neoadjuvant chemotherapy (NAC) using proteomics, genomics and histopathology. We show that the pre-, on-treatment and dynamic changes of the immune state, tumor metabolic proteins and tumor cell gene expression profiling-based metabolic phenotype are associated with treatment response. Single-cell/nucleus RNA sequencing revealed distinct tumor and immune cell states in metabolism between cold and hot tumors. Potential drivers of NAC based on above analyses were validated in vitro. In summary, the study shows that the interaction of tumor-intrinsic metabolic states and TME is associated with treatment outcome, supporting the concept of targeting tumor metabolism for immunoregulation.

An integrated omics approach highlights how epigenetic events can explain and predict response to neoadjuvant chemotherapy and bevacizumab in breast cancer.

Treatment with the anti-angiogenic drug bevacizumab in addition to chemotherapy has shown efficacy for breast cancer in some clinical trials, but better biomarkers are needed to optimally select patients for treatment. Here, we present an omics approach where DNA methylation profiles are integrated with gene expression and results from proteomic data in breast cancer patients to predict response to therapy and pinpoint response-related epigenetic events. Fresh-frozen tumor biopsies taken before, during, and after treatment from human epidermal growth factor receptor 2 negative non-metastatic patients receiving neoadjuvant chemotherapy with or without bevacizumab were subjected to molecular profiling. Here, we report that DNA methylation at enhancer CpGs related to cell cycle regulation can predict response to chemotherapy and bevacizumab for the estrogen receptor positive subset of patients (AUC = 0.874), and we validated this observation in an independent patient cohort with a similar treatment regimen (AUC = 0.762). Combining the DNA methylation scores with the scores from a previously published protein signature resulted in a slight increase in the prediction performance (AUC = 0.784). We also show that tumors receiving the combination treatment underwent more extensive epigenetic alterations. Finally, we performed an integrative expression-methylation quantitative trait loci analysis on alterations in DNA methylation and gene expression levels, showing that the epigenetic alterations that occur during treatment are different between responders and non-responders and that these differences may be explained by the proliferation-epithelial-to-mesenchymal transition axis through the activity of grainyhead like transcription factor 2. Using tumor purity computed from copy number data, we developed a method for estimating cancer cell-specific methylation to confirm that the association to response reflects DNA methylation in cancer cells. Taken together, these results support the potential for clinical benefit of the addition of bevacizumab to chemotherapy when administered to the correct patients.

The role of serum thymidine kinase 1 activity in neoadjuvant-treated HER2-positive breast cancer: biomarker analysis from the Swedish phase II randomized PREDIX HER2 trial.

BACKGROUND: Thymidine kinase 1 (TK1) plays a pivotal role in DNA synthesis and cellular proliferation. TK1 has been studied as a prognostic marker and as an early indicator of treatment response in human epidermal growth factor 2 (HER2)-negative early and metastatic breast cancer (BC). However, the prognostic and predictive value of serial TK1 activity in HER2-positive BC remains unknown. METHODS: In the PREDIX HER2 trial, 197 HER2-positive BC patients were randomized to neoadjuvant trastuzumab, pertuzumab, and docetaxel (DPH) or trastuzumab emtansine (T-DM1), followed by surgery and adjuvant epirubicin and cyclophosphamide. Serum samples were prospectively collected from all participants at multiple timepoints: at baseline, after cycle 1, 2, 4, and 6, at end of adjuvant therapy, annually for a total period of 5 years and/or at the time of recurrence. The associations of sTK1 activity with baseline characteristics, pathologic complete response (pCR), event-free survival (EFS), and disease-free survival (DFS) were evaluated. RESULTS: No association was detected between baseline sTK1 levels and all the baseline clinicopathologic characteristics. An increase of TK1 activity from baseline to cycle 2 was seen in all cases. sTK1 level at baseline, after 2 and 4 cycles was not associated with pCR status. After a median follow-up of 58 months, 23 patients had EFS events. There was no significant effect between baseline or cycle 2 sTK1 activity and time to event. A non-significant trend was noted among patents with residual disease (non-pCR) and high sTK1 activity at the end of treatment visit, indicating a potentially worse long-term prognosis. CONCLUSION: sTK1 activity increased following neoadjuvant therapy for HER2-positive BC but was not associated with patient outcomes or treatment benefit. However, the post-surgery prognostic value in patients that have not attained pCR warrants further investigation. TRIAL REGISTRATION: ClinicalTrials.gov, NCT02568839. Registered on 6 October 2015.

Multiresolution Self-Supervised Feature Integration via Attention Multiple Instance Learning for Histopathology Analysis.

Digital histopathology image analysis of tumor tissue sections has seen great research interest for automating standard diagnostic tasks, but also for developing novel prognostic biomarkers. However, research has mainly been focused on developing uniresolution models, capturing either high-resolution cellular features or low-resolution tissue architectural features. In addition, in the patch-based weakly-supervised training of deep learning models, the features which represent the intratumoral heterogeneity are lost. In this study, we propose a multiresolution attention-based multiple instance learning framework that can capture cellular and contextual features from the whole tissue for predicting patient-level outcomes. Several basic mathematical operations were examined for integrating multiresolution features, i.e. addition, mean, multiplication and concatenation. The proposed multiplication-based multiresolution model performed the best (AUC=0.864), while all multiresolution models outperformed the uniresolution baseline models (AUC=0.669, 0.713) for breast-cancer grading. (Implementation: https://github.com/tsikup/multiresolution-clam).

Breast cancer survival and incidence of second primary cancers after 30 years in a randomized study of two versus five years of adjuvant tamoxifen therapy.

BACKGROUND: Tamoxifen is an established treatment for breast cancer, but its long-term effects on survival and on secondary cancers are not fully evaluated. MATERIAL AND METHODS: We studied 30 years outcome of 4124 postmenopausal patients who were randomized to receive (totally) two or five years of adjuvant tamoxifen. RESULTS: After 5 years of follow-up, when tamoxifen treatment was finished in both groups, until 15 years of follow-up, overall mortality (HR 0.80, 95% CI 0.72-0.90, p < 0.001), breast cancer mortality for all patients (HR 0.80, 95% CI 0.68-0.94, p = 0.006) and breast cancer mortality for patients with estrogen receptor positive disease (HR 0.67, 95% CI 0.55-0.83, p < 0.001) were significantly reduced in the five-year group as compared to the two-year group. After 15 years, the difference remained but did not further increase. In the five-year group, the incidence of contralateral breast cancer was gradually reduced during the entire period of observation. The incidence of lung cancer was also reduced in the five-year group. In contrast there was an increased endometrial cancer incidence in the five-year group and for those receiving 40 mg of tamoxifen this incidence was further increased. CONCLUSION: Three more years of tamoxifen therapy reduced the risk of breast cancer mortality. The difference was established during the first 15 years after randomization. Moreover, the incidence of contralateral breast cancer gradually decreased for 30 years. The incidence of lung cancer was reduced in the five-year group. In contrast the incidence of endometrial cancer was increased.

CD169+ Macrophages in Primary Breast Tumors Associate with Tertiary Lymphoid Structures, Tregs and a Worse Prognosis for Patients with Advanced Breast Cancer.

The presence of CD169+ macrophages in the draining lymph nodes of cancer patients is, for unknown reasons, associated with a beneficial prognosis. We here investigated the prognostic impact of tumor-infiltrating CD169+ macrophages in primary tumors (PTs) and their spatial relation to tumor-infiltrating B and T cells. Using two breast cancer patient cohorts, we show that CD169+ macrophages were spatially associated with the presence of B and T cell tertiary lymphoid-like structures (TLLSs) in both PTs and lymph node metastases (LNMs). While co-infiltration of CD169+/TLLS in PTs correlated with a worse prognosis, the opposite was found when present in LNMs. RNA sequencing of breast tumors further confirmed that SIGLEC1 (CD169) expression was associated with mature tertiary lymphoid structure (TLS), and Treg and Breg signatures. We propose that the negative prognostic value related to CD169+ macrophages in PTs is a consequence of an immunosuppressive tumor environment rich in TLSs, Tregs and Bregs.

Survival Outcomes, Digital TILs, and On-treatment PET/CT During Neoadjuvant Therapy for HER2-positive Breast Cancer: Results from the Randomized PREDIX HER2 Trial.

PURPOSE: PREDIX HER2 is a randomized Phase II trial that compared neoadjuvant docetaxel, trastuzumab, and pertuzumab (THP) with trastuzumab emtansine (T-DM1) for HER2-positive breast cancer. Rates of pathologic complete response (pCR) did not differ between the two groups. Here, we present the survival outcomes from PREDIX HER2 and investigate metabolic response and tumor-infiltrating lymphocytes (TIL) as prognostic factors. PATIENTS AND METHODS: In total, 202 patients with HER2-positive breast cancer were enrolled and 197 patients received six cycles of either THP or T-DM1. Secondary endpoints included event-free survival (EFS), recurrence-free survival (RFS), and overall survival (OS). Assessment with PET/CT was performed at baseline, after two and six treatment cycles. TILs were assessed manually at baseline biopsies, while image-based evaluation of TILs [digital TILs (DTIL)] was performed in digitized full-face sections. RESULTS: After a median follow-up of 5.21 years, there was no difference between the two treatment groups in terms of EFS [HR = 1.26; 95% confidence interval (CI), 0.54-2.91], RFS (HR = 0.69; 95% CI, 0.24-1.93), or OS (HR = 0.52; 95% CI, 0.09-2.82). Higher SUVmax at cycle 2 (C2) predicted lower pCR (ORadj = 0.65; 95% CI, 0.48-0.87; P = 0.005) and worse EFS (HRadj = 1.27; 95% CI, 1.12-1.41; P < 0.001). Baseline TILs and DTILs provided additional prognostic information to clinical parameters and C2 SUVmax. CONCLUSIONS: Long-term outcomes following neoadjuvant T-DM1 were similar to neoadjuvant THP. SUVmax after two cycles of neoadjuvant therapy for HER2-positive breast cancer may be an independent predictor of both short- and long-term outcomes. Combined assessment with TILs may facilitate early selection of poor responders for alternative treatment strategies.

Adjuvant trastuzumab emtansine in HER2-positive breast cancer patients with HER2-negative residual invasive disease in KATHERINE.

Following chemotherapy and human epidermal growth factor 2 (HER2)-targeted neoadjuvant therapy for HER2-positive early breast cancer, residual invasive breast cancer at surgery may be HER2-negative on retesting in some patients. We evaluated outcomes with T-DM1 and trastuzumab in patients randomized in the phase III KATHERINE trial based on HER2-positive central testing of the pre-treatment core biopsy with HER2-negative central testing on their corresponding surgical specimen after neoadjuvant treatment. In the 70/845 (8.3%) patients with HER2-negative residual disease on retesting at surgery, there were 11 IDFS events in the 42 trastuzumab-treated patients (26.2%) and none in the 28 T-DM1-treated patients, suggesting that T-DM1 should not be withheld in this patient population.

Discordance of PD-L1 Expression at the Protein and RNA Levels in Early Breast Cancer.

We aimed to assess if the discrepant prognostic information between Programmed Death Ligand 1 (PD-L1) protein versus mRNA expression in early breast cancer (BC) could be attributed to heterogeneity in its expression. PD-L1 protein and mRNA expression in BC tissue microarrays from two clinical patient cohorts were evaluated (105 patients; cohort 1: untreated; cohort 2: neoadjuvant chemotherapy-treated). Immunohistochemistry (IHC) with SP142, SP263 was performed. PD-L1 mRNA was evaluated using bulk gene expression and RNA-FISH RNAscope®, the latter scored in a semi-quantitative manner and combined with immunofluorescence (IF) staining for the simultaneous detection of PD-L1 protein expression. PD-L1 expression was assessed in cores as a whole and in two regions of interest (ROI) from the same core. The cell origin of PD-L1 expression was evaluated using multiplex fluorescent IHC. IHC PD-L1 expression between SP142 and SP263 was concordant in 86.7% of cores (p < 0.001). PD-L1 IF/IHC was weakly correlated with spatial mRNA expression (concordance 54.6-71.2%). PD-L1 was mostly expressed by lymphocytes intra-tumorally, while its stromal expression was mostly observed in macrophages. Our results demonstrate only moderate concordance between the various methods of assessing PD-L1 expression at the protein and mRNA levels, which may be attributed to both analytical performance and spatial heterogeneity.

Neoadjuvant Trastuzumab, Pertuzumab, and Docetaxel vs Trastuzumab Emtansine in Patients With ERBB2-Positive Breast Cancer: A Phase 2 Randomized Clinical Trial.

Importance: Trastuzumab emtansine (T-DM1) is presently approved for treatment of advanced breast cancer and after incomplete response to neoadjuvant therapy, but the potential of T-DM1 as monotherapy is so far unknown. Objective: To assess pathologic complete response (pCR) to standard neoadjuvant therapy of combination docetaxel, trastuzumab, and pertuzumab (DTP) vs T-DM1 monotherapy in patients with ERBB2 (formerly HER2)-positive breast cancer. Design, Setting, and Participants: This randomized phase 2 trial, conducted at 9 sites in Sweden, enrolled 202 patients between December 1, 2014, and October 31, 2018. Participants were 18 years or older, with ERBB2-positive tumors larger than 20 mm and/or verified lymph node metastases. Analysis was performed on an intention-to-treat basis. Interventions: Patients were randomized to receive 6 cycles of DTP (standard group) or T-DM1 (investigational group). Crossover was recommended at lack of response or occurrence of intolerable toxic effects. Assessment with fluorine 18-labeled fluorodeoxyglucose (18F-FDG) positron emission tomography combined with computed tomography (PET-CT) was performed at baseline and after 2 and 6 treatment cycles. Main Outcome and Measures: Pathologic complete response, defined as ypT0 or Tis ypN0. Secondary end points were clinical and radiologic objective response; event-free survival, invasive disease-free survival, distant disease-free survival, and overall survival; safety; health-related quality of life (HRQoL); functional and biological tumor characteristics; and frequency of breast-conserving surgery. Results: Overall, 202 patients were randomized; 197 (99 women in the standard group [median age, 51 years (range, 26-73 years)] and 98 women in the investigational group [median age, 53 years (range, 28-74 years)]) were evaluable for the primary end point. Pathologic complete response was achieved in 45 patients in the standard group (45.5%; 95% CI 35.4%-55.8%) and 43 patients in the investigational group (43.9%; 95% CI 33.9%-54.3%). The difference was not statistically significant (P = .82). In a subgroup analysis, the pCR rate was higher in hormone receptor-negative tumors than in hormone receptor-positive tumors in both treatment groups (45 of 72 [62.5%] vs 45 of 125 [36.0%]). Three patients in the T-DM1 group experienced progression during therapy. In an exploratory analysis, tumor-infiltrating lymphocytes at 10% or more (median) estimated pCR significantly (odds ratio, 2.76; 95% CI, 1.42-5.36; P = .003). Response evaluation with 18F-FDG PET-CT revealed a relative decrease of maximum standardized uptake value by equal to or greater than 68.7% (median) was associated with pCR (odds ratio, 6.74, 95% CI, 2.75-16.51; P < .001). Conclusions and Relevance: In this study, treatment with standard neoadjuvant combination DTP was equal to T-DM1. Trial Registrations: ClinicalTrials.gov Identifier: NCT02568839; EudraCT number: 2014-000808-10.

Protein Signature Predicts Response to Neoadjuvant Treatment With Chemotherapy and Bevacizumab in HER2-Negative Breast Cancers.

PURPOSE: Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS: In the NeoAva phase II clinical trial, patients (N = 132) with large (≥ 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS: We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P < .001) and in patients with low RCB (P < .001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). CONCLUSION: Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.

Transcriptomic and functional pathway features were associated with survival after pathological complete response to neoadjuvant chemotherapy in breast cancer.

Pathological complete response (pCR) after neoadjuvant chemotherapy (NAC) has been proposed as a surrogate endpoint for the prediction of long-term survival in breast cancer (BC); however, an increased pCR rate has not clearly correlated with improved survival. We hypothesized that some transcriptomic and functional pathway features correlate with survival after pCR in BC. We utilized 2 published NAC cohorts, 105 women with gene expression data before, "Baseline", and that changed during NAC, "Delta", and TCGA database with 1068 BC patients to investigate the relationship between the efficacy of NAC and survival utilizing differentially expressed-mRNAs, construction and analysis of the mRNA-hub gene network, and functional pathway analysis. In mRNA expression profiling, S100A8 was a gene involved in survival after pCR in Baseline and NDP was a gene involved in recurrence after pCR in Delta. In functional pathway analysis, we found multiple pathways involved in survival after pCR. In mRNA-hub gene analysis, HSP90AA1, EEF1A1, APP, and HSPA4 were related to recurrence in BC patients with pCR due to NAC. TP53, EGFR, CTNNB1, ERBB2, and HSPB1 may play a significant role in survival for patients with pCR. Interestingly, high HSP90AA1, HSPA4, S100A8, and TP53, and low EEF1A1, EGFR, and CTNNB1 expressing tumors have significantly worse overall survival in TCGA BC cohort. We demonstrated the genes and functional pathway features associated with pCR and survival utilizing the bioinformatics approach to public BC cohorts. Some genes involved in recurrence after pCR due to NAC also served as prognostic factors in primary BC.

Separation of breast cancer and organ microenvironment transcriptomes in metastases.

BACKGROUND: The seed and soil hypothesis was proposed over a century ago to describe why cancer cells (seeds) grow in certain organs (soil). Since then, the genetic properties that define the cancer cells have been heavily investigated; however, genomic mediators within the organ microenvironment that mediate successful metastatic growth are less understood. These studies sought to identify cancer- and organ-specific genomic programs that mediate metastasis. METHODS: In these studies, a set of 14 human breast cancer patient-derived xenograft (PDX) metastasis models was developed and then tested for metastatic tropism with two approaches: spontaneous metastases from mammary tumors and intravenous injection of PDX cells. The transcriptomes of the cancer cells when growing as tumors or metastases were separated from the transcriptomes of the microenvironment via species-specific separation of the genomes. Drug treatment of PDX spheroids was performed to determine if genes activated in metastases may identify targetable mediators of viability. RESULTS: The experimental approaches that generated metastases in PDX models were identified. RNA sequencing of 134 tumors, metastases, and normal non-metastatic organs identified cancer- and organ-specific genomic properties that mediated metastasis. A common genomic response of the liver microenvironment was found to occur in reaction to the invading PDX cells. Genes within the cancer cells were found to be either transiently regulated by the microenvironment or permanently altered due to clonal selection of metastatic sublines. Gene Set Enrichment Analyses identified more than 400 gene signatures that were commonly activated in metastases across basal-like PDXs. A Src signaling signature was found to be extensively upregulated in metastases, and Src inhibitors were found to be cytotoxic to PDX spheroids. CONCLUSIONS: These studies identified that during the growth of breast cancer metastases, there were genomic changes that occurred within both the cancer cells and the organ microenvironment. We hypothesize that pathways upregulated in metastases are mediators of viability and that simultaneously targeting changes within different cancer cell pathways and/or different tissue compartments may be needed for inhibition of disease progression.

Protein profiling of fine-needle aspirates reveals subtype-associated immune signatures and involvement of chemokines in breast cancer.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and for follow-up of personalized cancer therapy, including immunotherapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissue samples; however, the minute amounts of sample require sensitive multiplex molecular analysis to be of clinical biomarker utility. We have applied proximity extension assays (PEA) to analyze 167 proteins in FNA samples from patients with breast cancer (BC; n = 25) and benign lesions (n = 32). We demonstrate that the FNA BC samples could be divided into two main clusters, characterized by differences in expression levels of the estrogen receptor (ER) and the proliferation marker Ki67. This clustering corresponded to some extent to established BC subtypes. Our analysis also revealed several proteins whose expression levels differed between BC and benign lesions (e.g., CA9, GZMB, IL-6, VEGFA, CXCL11, PDL1, and PCD1), as well as several chemokines correlating with ER and Ki67 status (e.g., CCL4, CCL8, CCL20, CXCL8, CXCL9, and CXCL17). Finally, we also identified three signatures that could predict Ki67 status, ER status, and tumor grade, respectively, based on a small subset of proteins, which was dominated by chemokines. To our knowledge, expression profiles of CCL13 in benign lesions and BC have not previously been described but were shown herein to correlate with proliferation (P = 0.00095), suggesting a role in advanced BC. Given the broad functional range of the proteins analyzed, immune-related proteins were overrepresented among the observed alterations. Our pilot study supports the emerging role of chemokines in BC progression. Due to the minimally traumatic sampling and clinically important molecular information for therapeutic decisions, this methodology is promising for future immunoscoring and monitoring of treatment efficacy in BC.

Pharmacogenetic impact of docetaxel on neoadjuvant treatment of breast cancer patients.

AIM: This study aimed to investigate the effect of CYP3A4 and CYP3A5 genotypes on clinical outcomes of docetaxel treatment. PATIENTS & METHODS: In the PROMIX trial, 150 breast cancer patients received docetaxel preoperatively. CYP3A4 and CYP3A5 genotype combinations were transformed into total CYP 3A phenotypes. RESULTS: Seven patients were characterized as poor metabolizer (PM), 22 patients as extensive metabolizer and 121 patients as intermediate metabolizer. The frequency of grade 3/grade 4 adverse events was higher in the PM group (p = 0.002). One PM subject who basically lacked enzyme activity died from typhlitis. Total 45 recurrences were reported after a median of 5-year follow-up; none of these was PM. CONCLUSION: The allelic variants CYP3A4*22 and CYP3A5*3 contribute to the interpatient variations of docetaxel.

Dynamic evaluation of the immune infiltrate and immune function genes as predictive markers for neoadjuvant chemotherapy in hormone receptor positive, HER2 negative breast cancer.

Gene expression (GE) signatures and Tumor Infiltrating Lymphocytes (TIL) enumeration are predictive for response to neoadjuvant chemotherapy in HR- and in HER2+ breast cancer, but data are conflicting in HR+/HER2- disease. This study aimed to explore their predictive value in this subset, measured both at baseline and after short exposure to chemotherapy. Specifically, the PROMIX phase 2 trial enrolled patients with locally advanced HER2- BC to receive six cycles of epirubicin and docetaxel, plus bevacizumab during cycles 3-6. Patients underwent tumor biopsies at baseline and after cycle 2 for GE profiling and enumeration of TIL, FOXP3+ T-cells and CD163+ macrophages. An immune related gene module and the quantification of the immune infiltrate were analyzed for association with pathologic complete response (pCR), decrease in tumor size and disease-free survival (DFS). Of the 150 patients enrolled in PROMIX, 113 were HR+/HER2-. Baseline GE and immune cell enumeration data were available from 71 patients, while data after 2 cycles of chemotherapy were available from 41. At baseline, only GE was statistically significantly associated with higher pCR rates (OR 2.29, 95% CI 1.05 - 5.38, p = 0.037) and decrease in tumor size (r = 0.25, p = 0.047). In contrast, longitudinal data indicate that both GE (r = 0.54, p<0.001) and TIL abundance (p = 0.009) are stronger predictors for the reduction of tumor size, while low FOXP3+ was statistically significantly associated with an improved DFS (p = 0.027). In conclusion, GE analysis, TIL and FOXP3+ enumeration after short-term exposure to chemotherapy carry important predictive information in HR+/HER2- breast cancer at the neoadjuvant setting.

A fine-needle aspiration-based protein signature discriminates benign from malignant breast lesions.

There are increasing demands for informative cancer biomarkers, accessible via minimally invasive procedures, both for initial diagnostics and to follow-up personalized cancer therapy. Fine-needle aspiration (FNA) biopsy provides ready access to relevant tissues; however, the minute sample amounts require sensitive multiplex molecular analysis to achieve clinical utility. We have applied proximity extension assays (PEA) and NanoString (NS) technology for analyses of proteins and of RNA, respectively, in FNA samples. Using samples from patients with breast cancer (BC, n = 25) or benign lesions (n = 33), we demonstrate that these FNA-based molecular analyses (a) can offer high sensitivity and reproducibility, (b) may provide correct diagnosis in shorter time and at a lower cost than current practice, (c) correlate with results from routine analysis (i.e., benchmarking against immunohistochemistry tests for ER, PR, HER2, and Ki67), and (d) may also help identify new markers related to immunotherapy. A specific 11-protein signature, including FGF binding protein 1, decorin, and furin, distinguished all cancer patient samples from all benign lesions in our main cohort and in smaller replication cohort. Due to the minimally traumatic sampling and rich molecular information, this combined proteomics and transcriptomic methodology is promising for diagnostics and evaluation of treatment efficacy in BC.

Chemoresistance Evolution in Triple-Negative Breast Cancer Delineated by Single-Cell Sequencing.

Triple-negative breast cancer (TNBC) is an aggressive subtype that frequently develops resistance to chemotherapy. An unresolved question is whether resistance is caused by the selection of rare pre-existing clones or alternatively through the acquisition of new genomic aberrations. To investigate this question, we applied single-cell DNA and RNA sequencing in addition to bulk exome sequencing to profile longitudinal samples from 20 TNBC patients during neoadjuvant chemotherapy (NAC). Deep-exome sequencing identified 10 patients in which NAC led to clonal extinction and 10 patients in which clones persisted after treatment. In 8 patients, we performed a more detailed study using single-cell DNA sequencing to analyze 900 cells and single-cell RNA sequencing to analyze 6,862 cells. Our data showed that resistant genotypes were pre-existing and adaptively selected by NAC, while transcriptional profiles were acquired by reprogramming in response to chemotherapy in TNBC patients.

Exome sequencing of primary breast cancers with paired metastatic lesions reveals metastasis-enriched mutations in the A-kinase anchoring protein family (AKAPs).

BACKGROUND: Tumor heterogeneity in breast cancer tumors is today widely recognized. Most of the available knowledge in genetic variation however, relates to the primary tumor while metastatic lesions are much less studied. Many studies have revealed marked alterations of standard prognostic and predictive factors during tumor progression. Characterization of paired primary- and metastatic tissues should therefore be fundamental in order to understand mechanisms of tumor progression, clonal relationship to tumor evolution as well as the therapeutic aspects of systemic disease. METHODS: We performed full exome sequencing of primary breast cancers and their metastases in a cohort of ten patients and further confirmed our findings in an additional cohort of 20 patients with paired primary and metastatic tumors. Furthermore, we used gene expression from the metastatic lesions and a primary breast cancer data set to study the gene expression of the AKAP gene family. RESULTS: We report that somatic mutations in A-kinase anchoring proteins are enriched in metastatic lesions. The frequency of mutation in the AKAP gene family was 10% in the primary tumors and 40% in metastatic lesions. Several copy number variations, including deletions in regions containing AKAP genes were detected and showed consistent patterns in both investigated cohorts. In a second cohort containing 20 patients with paired primary and metastatic lesions, AKAP mutations showed an increasing variant allele frequency after multiple relapses. Furthermore, gene expression profiles from the metastatic lesions (n = 120) revealed differential expression patterns of AKAPs relative to the tumor PAM50 intrinsic subtype, which were most apparent in the basal-like subtype. This pattern was confirmed in primary tumors from TCGA (n = 522) and in a third independent cohort (n = 182). CONCLUSION: Several studies from primary cancers have reported individual AKAP genes to be associated with cancer risk and metastatic relapses as well as direct involvement in cellular invasion and migration processes. Our findings reveal an enrichment of mutations in AKAP genes in metastatic breast cancers and suggest the involvement of AKAPs in the metastatic process. In addition, we report an AKAP gene expression pattern that consistently follows the tumor intrinsic subtype, further suggesting AKAP family members as relevant players in breast cancer biology.

Immune gene expression and response to chemotherapy in advanced breast cancer.

BACKGROUND: Transcriptomic profiles have shown promise as predictors of response to neoadjuvant chemotherapy in breast cancer (BC). This study aimed to explore their predictive value in the advanced BC (ABC) setting. METHODS: In a Phase 3 trial of first-line chemotherapy in ABC, a fine needle aspiration biopsy (FNAB) was obtained at baseline. Intrinsic molecular subtypes and gene modules related to immune response, proliferation, oestrogen receptor (ER) signalling and recurring genetic alterations were analysed for association with objective response to chemotherapy. Gene-set enrichment analysis (GSEA) of responders vs non-responders was performed independently. Lymphocytes were enumerated in FNAB smears and the absolute abundance of immune cell types was calculated using the Microenvironment Cell Populations counter method. RESULTS: Gene expression data were available for 109 patients. Objective response to chemotherapy was statistically significantly associated with an immune module score (odds ratio (OR)=1.62; 95% confidence interval (CI), 1.03-2.64; P=0.04). Subgroup analysis showed that this association was restricted to patients with ER-positive or luminal tumours (OR=3.54; 95%, 1.43-10.86; P=0.012 and P for interaction=0.04). Gene-set enrichment analysis confirmed that in these subgroups, immune-related gene sets were enriched in responders. CONCLUSIONS: Immune-related transcriptional signatures may predict response to chemotherapy in ER-positive and luminal ABC.