Tumor-Infiltrating Lymphocytes in Triple-Negative Breast Cancer.

Importance: The association of tumor-infiltrating lymphocyte (TIL) abundance in breast cancer tissue with cancer recurrence and death in patients with early-stage triple-negative breast cancer (TNBC) who are not treated with adjuvant or neoadjuvant chemotherapy is unclear. Objective: To study the association of TIL abundance in breast cancer tissue with survival among patients with early-stage TNBC who were treated with locoregional therapy but no chemotherapy. Design, Setting, and Participants: Retrospective pooled analysis of individual patient-level data from 13 participating centers in North America (Rochester, Minnesota; Vancouver, British Columbia, Canada), Europe (Paris, Lyon, and Villejuif, France; Amsterdam and Rotterdam, the Netherlands; Milan, Padova, and Genova, Italy; Gothenburg, Sweden), and Asia (Tokyo, Japan; Seoul, Korea), including 1966 participants diagnosed with TNBC between 1979 and 2017 (with follow-up until September 27, 2021) who received treatment with surgery with or without radiotherapy but no adjuvant or neoadjuvant chemotherapy. Exposure: TIL abundance in breast tissue from resected primary tumors. Main Outcomes and Measures: The primary outcome was invasive disease-free survival [iDFS]. Secondary outcomes were recurrence-free survival [RFS], survival free of distant recurrence [distant RFS, DRFS], and overall survival. Associations were assessed using a multivariable Cox model stratified by participating center. Results: This study included 1966 patients with TNBC (median age, 56 years [IQR, 39-71]; 55% had stage I TNBC). The median TIL level was 15% (IQR, 5%-40%). Four-hundred seventeen (21%) had a TIL level of 50% or more (median age, 41 years [IQR, 36-63]), and 1300 (66%) had a TIL level of less than 30% (median age, 59 years [IQR, 41-72]). Five-year DRFS for stage I TNBC was 94% (95% CI, 91%-96%) for patients with a TIL level of 50% or more, compared with 78% (95% CI, 75%-80%) for those with a TIL level of less than 30%; 5-year overall survival was 95% (95% CI, 92%-97%) for patients with a TIL level of 50% or more, compared with 82% (95% CI, 79%-84%) for those with a TIL level of less than 30%. At a median follow-up of 18 years, and after adjusting for age, tumor size, nodal status, histological grade, and receipt of radiotherapy, each 10% higher TIL increment was associated independently with improved iDFS (hazard ratio [HR], 0.92 [0.89-0.94]), RFS (HR, 0.90 [0.87-0.92]), DRFS (HR, 0.87 [0.84-0.90]), and overall survival (0.88 [0.85-0.91]) (likelihood ratio test, P < 10e-6). Conclusions and Relevance: In patients with early-stage TNBC who did not undergo adjuvant or neoadjuvant chemotherapy, breast cancer tissue with a higher abundance of TIL levels was associated with significantly better survival. These results suggest that breast tissue TIL abundance is a prognostic factor for patients with early-stage TNBC.

Impact of dose reductions on adjuvant abemaciclib efficacy for patients with high-risk early breast cancer: analyses from the monarchE study.

In monarchE, adjuvant abemaciclib significantly improved invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS), with sustained benefit beyond the 2-year treatment period. Abemaciclib dose reductions were allowed to proactively manage adverse events. Exploratory analyses to investigate the impact of dose reductions on efficacy were conducted. Across the three patient subgroups as defined by relative dose intensity (≤66%, 66-93%, ≥93%), the estimated 4-year IDFS rates were generally consistent (87.1%, 86.4%, and 83.7%, respectively). In the time-dependent Cox proportional hazard model, the effect of abemaciclib was consistent at the full dose compared to being reduced to a lower dose (IDFS hazard ratio: 0.905; 95% confidence interval: 0.727, 1.125; DRFS hazard ratio: 0.942; 95% confidence interval: 0.742, 1.195). These analyses showed that the efficacy of adjuvant abemaciclib was not compromised by protocol mandated dose reductions for patients with node positive, hormone receptor positive, human epidermal growth factor 2-negative, high-risk early breast cancer.

OmicsFootPrint: a framework to integrate and interpret multi-omics data using circular images and deep neural networks.

The OmicsFootPrint framework addresses the need for advanced multi-omics data analysis methodologies by transforming data into intuitive two-dimensional circular images and facilitating the interpretation of complex diseases. Utilizing Deep Neural Networks and incorporating the SHapley Additive exPlanations (SHAP) algorithm, the framework enhances model interpretability. Tested with The Cancer Genome Atlas (TCGA) data, OmicsFootPrint effectively classified lung and breast cancer subtypes, achieving high Area Under Curve (AUC) scores - 0.98±0.02 for lung cancer subtype differentiation, 0.83±0.07 for breast cancer PAM50 subtypes, and successfully distinguishe between invasive lobular and ductal carcinomas in breast cancer, showcasing its robustness. It also demonstrated notable performance in predicting drug responses in cancer cell lines, with a median AUC of 0.74, surpassing existing algorithms. Furthermore, its effectiveness persists even with reduced training sample sizes. OmicsFootPrint marks an enhancement in multi-omics research, offering a novel, efficient, and interpretable approach that contributes to a deeper understanding of disease mechanisms.

Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer.

Operable triple-negative breast cancer (TNBC) has a higher risk of recurrence and death compared to other subtypes. Tumor size and nodal status are the primary clinical factors used to guide systemic treatment, while biomarkers of proliferation have not demonstrated value. Recent studies suggest that subsets of TNBC have a favorable prognosis, even without systemic therapy. We evaluated the association of fully automated mitotic spindle hotspot (AMSH) counts with recurrence-free (RFS) and overall survival (OS) in two separate cohorts of patients with early-stage TNBC who did not receive systemic therapy. AMSH counts were obtained from areas with the highest mitotic density in digitized whole slide images processed with a convolutional neural network trained to detect mitoses. In 140 patients from the Mayo Clinic TNBC cohort, AMSH counts were significantly associated with RFS and OS in a multivariable model controlling for nodal status, tumor size, and tumor-infiltrating lymphocytes (TILs) (p < 0.0001). For every 10-point increase in AMSH counts, there was a 16% increase in the risk of an RFS event (HR 1.16, 95% CI 1.08-1.25), and a 7% increase in the risk of death (HR 1.07, 95% CI 1.00-1.14). We corroborated these findings in a separate cohort of systemically untreated TNBC patients from Radboud UMC in the Netherlands. Our findings suggest that AMSH counts offer valuable prognostic information in patients with early-stage TNBC who did not receive systemic therapy, independent of tumor size, nodal status, and TILs. If further validated, AMSH counts could help inform future systemic therapy de-escalation strategies.

Adjuvant Abemaciclib Plus Endocrine Therapy for Hormone Receptor-Positive, Human Epidermal Growth Factor Receptor 2-Negative, High-Risk Early Breast Cancer: Results From a Preplanned monarchE Overall Survival Interim Analysis, Including 5-Year Efficacy Outcomes.

Clinical trials frequently include multiple end points that mature at different times. The initial report, typically based on the primary end point, may be published when key planned co-primary or secondary analyses are not yet available. Clinical trial updates provide an opportunity to disseminate additional results from studies, published in JCO or elsewhere, for which the primary end point has already been reported.Two years of adjuvant abemaciclib combined with endocrine therapy (ET) resulted in a significant improvement in invasive disease-free survival (IDFS) and distant relapse-free survival (DRFS) that persisted beyond the 2-year treatment period in patients with hormone receptor-positive, human epidermal growth factor receptor 2-negative, node-positive, high-risk early breast cancer (EBC). Here, we report 5-year efficacy results from a prespecified overall survival (OS) interim analysis. In the intent-to-treat population, with a median follow-up of 54 months, the benefit of abemaciclib was sustained with hazard ratios of 0.680 (95% CI, 0.599 to 0.772) for IDFS and 0.675 (95% CI, 0.588 to 0.774) for DRFS. This persistence of abemaciclib benefit translated to continuous separation of the curves with a deepening in 5-year absolute improvement in IDFS and DRFS rates of 7.6% and 6.7%, respectively, compared with rates of 6% and 5.3% at 4 years and 4.8% and 4.1% at 3 years. With fewer deaths in the abemaciclib plus ET arm compared with the ET-alone arm (208 v 234), statistical significance was not reached for OS. No new safety signals were observed. In conclusion, abemaciclib plus ET continued to reduce the risk of developing invasive and distant disease recurrence beyond the completion of treatment. The increasing absolute improvement at 5 years is consistent with a carryover effect and further supports the use of abemaciclib in patients with high-risk EBC.

Patient-specific signaling signatures predict optimal therapeutic combinations for triple negative breast cancer.

Triple negative breast cancer (TNBC) is a heterogeneous group of tumors which lack estrogen receptor, progesterone receptor, and HER2 expression. Targeted therapies have limited success in treating TNBC, thus a strategy enabling effective targeted combinations is an unmet need. To tackle these challenges and discover individualized targeted combination therapies for TNBC, we integrated phosphoproteomic analysis of altered signaling networks with patient-specific signaling signature (PaSSS) analysis using an information-theoretic, thermodynamic-based approach. Using this method on a large number of TNBC patient-derived tumors (PDX), we were able to thoroughly characterize each PDX by computing a patient-specific set of unbalanced signaling processes and assigning a personalized therapy based on them. We discovered that each tumor has an average of two separate processes, and that, consistent with prior research, EGFR is a major core target in at least one of them in half of the tumors analyzed. However, anti-EGFR monotherapies were predicted to be ineffective, thus we developed personalized combination treatments based on PaSSS. These were predicted to induce anti-EGFR responses or to be used to develop an alternative therapy if EGFR was not present.In-vivo experimental validation of the predicted therapy showed that PaSSS predictions were more accurate than other therapies. Thus, we suggest that a detailed identification of molecular imbalances is necessary to tailor therapy for each TNBC. In summary, we propose a new strategy to design personalized therapy for TNBC using pY proteomics and PaSSS analysis. This method can be applied to different cancer types to improve response to the biomarker-based treatment.

Identification of a Notch transcriptomic signature for breast cancer.

BACKGROUND: Dysregulated Notch signalling contributes to breast cancer development and progression, but validated tools to measure the level of Notch signalling in breast cancer subtypes and in response to systemic therapy are largely lacking. A transcriptomic signature of Notch signalling would be warranted, for example to monitor the effects of future Notch-targeting therapies and to learn whether altered Notch signalling is an off-target effect of current breast cancer therapies. In this report, we have established such a classifier. METHODS: To generate the signature, we first identified Notch-regulated genes from six basal-like breast cancer cell lines subjected to elevated or reduced Notch signalling by culturing on immobilized Notch ligand Jagged1 or blockade of Notch by γ-secretase inhibitors, respectively. From this cadre of Notch-regulated genes, we developed candidate transcriptomic signatures that were trained on a breast cancer patient dataset (the TCGA-BRCA cohort) and a broader breast cancer cell line cohort and sought to validate in independent datasets. RESULTS: An optimal 20-gene transcriptomic signature was selected. We validated the signature on two independent patient datasets (METABRIC and Oslo2), and it showed an improved coherence score and tumour specificity compared with previously published signatures. Furthermore, the signature score was particularly high for basal-like breast cancer, indicating an enhanced level of Notch signalling in this subtype. The signature score was increased after neoadjuvant treatment in the PROMIX and BEAUTY patient cohorts, and a lower signature score generally correlated with better clinical outcome. CONCLUSIONS: The 20-gene transcriptional signature will be a valuable tool to evaluate the response of future Notch-targeting therapies for breast cancer, to learn about potential effects on Notch signalling from conventional breast cancer therapies and to better stratify patients for therapy considerations.

Nodal pCR and overall survival following neoadjuvant chemotherapy for node positive ER+/Her2- breast cancer.

PURPOSE: The role of neoadjuvant chemotherapy (NAC) in node-positive (N+) ER+/HER2- breast cancer (BC) is debated, given low total pathologic complete response (pCR) rates. However, the rate and impact of nodal pCR is unknown. We sought to evaluate nodal pCR rates and the impact on overall survival (OS). Further, we sought to validate the association between nodal pCR with age and Ki67. METHODS: We queried the National Cancer Database for cN + ER+/HER2- BC patients treated with NAC and surgery. Data from 2010 to 2018 were used to evaluate nodal pCR and OS, with multivariable Cox proportional hazards modeling for OS, as well as Ki67 for the years 2018-2019. RESULTS: From 2010 to 2018, we identified 19,611 cN + ER+/HER2- BC patients treated with NAC. While total pCR occurred in only 7.4%, nodal pCR rates were nearly double (14.3%). Nodal pCR (+/- breast pCR) was seen in 21.7% and associated with 5-year OS rate of 86.1% (95% CI: 84.9-87.4%) versus 77.1% (95% CI: 76.3-77.9%) in patients without nodal pCR (p < 0.001). On multivariable analysis, nodal pCR had better OS (adjusted HR 0.57, 95% CI 0.52-0.63, p < 0.001) across all age groups. Of 2,444 patients with available Ki67, those with age < 50 and Ki67 ≥ 20% had the highest nodal pCR at 31.6%. CONCLUSION: In cN + ER+/HER2- BC treated with NAC, nodal pCR is common, associated with age and Ki67, and prognostic for OS. These data strongly suggest that for cN + patients, eradication of nodal disease is critical for OS, and total pCR may not be the optimal measure of NAC benefit.

Endoxifen downregulates AKT phosphorylation through protein kinase C beta 1 inhibition in ERα+ breast cancer.

Endoxifen, a secondary tamoxifen metabolite, is a potent antiestrogen exhibiting estrogen receptor alpha (ERα) binding at nanomolar concentrations. Phase I/II clinical trials identified clinical activity of Z-endoxifen (ENDX), in endocrine-refractory metastatic breast cancer as well as ERα+ solid tumors, raising the possibility that ENDX may have a second, ERα-independent, mechanism of action. An unbiased mass spectrometry approach revealed that ENDX concentrations achieved clinically with direct ENDX administration (5 µM), but not low concentrations observed during tamoxifen treatment (<0.1 µM), profoundly altered the phosphoproteome of the aromatase expressing MCF7AC1 cells with limited impact on the total proteome. Computational analysis revealed protein kinase C beta (PKCß) and protein kinase B alpha or AKT1 as potential kinases responsible for mediating ENDX effects on protein phosphorylation. ENDX more potently inhibited PKCß1 kinase activity compared to other PKC isoforms, and ENDX binding to PKCß1 was confirmed using Surface Plasma Resonance. Under conditions that activated PKC/AKT signaling, ENDX induced PKCß1 degradation, attenuated PKCß1-activated AKTSer473 phosphorylation, diminished AKT substrate phosphorylation, and induced apoptosis. ENDX's effects on AKT were phenocopied by siRNA-mediated PKCß1 knockdown or treatment with the pan-AKT inhibitor, MK-2206, while overexpression of constitutively active AKT diminished ENDX-induced apoptosis. These findings, which identify PKCß1 as an ENDX target, indicate that PKCß1/ENDX interactions suppress AKT signaling and induce apoptosis in breast cancer.

Landscape of baseline and acquired genomic alterations in circulating tumor DNA with abemaciclib alone or with endocrine therapy in advanced breast cancer.

PURPOSE: To identify potential predictors of response and resistance mechanisms in patients with hormone receptor-positive (HR+), human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer (ABC) treated with the CDK4/6 inhibitor abemaciclib +/- endocrine therapy (ET), baseline and acquired genomic alterations in circulating tumor DNA (ctDNA) were analyzed and associated with clinical outcomes. PATIENTS AND METHODS: MONARCH 3: postmenopausal women with HR+, HER2- ABC and no prior systemic therapy in the advanced setting were randomized to abemaciclib or placebo plus nonsteroidal aromatase inhibitor (NSAI). nextMONARCH: women with HR+, HER2- metastatic breast cancer that progressed on/after prior ET and chemotherapy were randomized to abemaciclib alone (two doses) or plus tamoxifen. Baseline and end-of-treatment plasma samples from patients in MONARCH 3 and nextMONARCH (monotherapy arms) were analyzed to identify somatic genomic alterations. Association between genomic alterations and median progression-free survival (mPFS) was assessed. RESULTS: Most patients had ≥1 genomic alteration detected in baseline ctDNA. In MONARCH 3, abemaciclib+NSAI was associated with improved mPFS versus placebo+NSAI, regardless of baseline alterations. ESR1 alterations were less frequently acquired in the abemaciclib+NSAI arm than placebo+NSAI. Acquired alterations potentially associated with resistance to abemaciclib +/- NSAI included RB1 and MYC. CONCLUSIONS: In MONARCH 3, certain baseline ctDNA genomic alterations were prognostic for ET but not predictive of abemaciclib response. Further studies are warranted to assess whether ctDNA alterations acquired during abemaciclib treatment differ from other CDK4/6 inhibitors. Findings are hypothesis-generating, further exploration is warranted into mechanisms of resistance to abemaciclib and ET.

Identifying homologous recombination deficiency in breast cancer: genomic instability score distributions differ among breast cancer subtypes.

PURPOSE: A 3-biomarker homologous recombination deficiency (HRD) score is a key component of a currently FDA-approved companion diagnostic assay to identify HRD in patients with ovarian cancer using a threshold score of ≥ 42, though recent studies have explored the utility of a lower threshold (GIS ≥ 33). The present study evaluated whether the ovarian cancer thresholds may also be appropriate for major breast cancer subtypes by comparing the genomic instability score (GIS) distributions of BRCA1/2-deficient estrogen receptor-positive breast cancer (ER + BC) and triple-negative breast cancer (TNBC) to the GIS distribution of BRCA1/2-deficient ovarian cancer. METHODS: Ovarian cancer and breast cancer (ER + BC and TNBC) tumors from ten study cohorts were sequenced to identify pathogenic BRCA1/2 mutations, and GIS was calculated using a previously described algorithm. Pathologic complete response (pCR) to platinum therapy was evaluated in a subset of TNBC samples. For TNBC, a threshold was set and threshold validity was assessed relative to clinical outcomes. RESULTS: A total of 560 ovarian cancer, 805 ER + BC, and 443 TNBC tumors were included. Compared to ovarian cancer, the GIS distribution of BRCA1/2-deficient samples was shifted lower for ER + BC (p = 0.015), but not TNBC (p = 0.35). In the subset of TNBC samples, univariable logistic regression models revealed that GIS status using thresholds of ≥ 42 and ≥ 33 were significant predictors of response to platinum therapy. CONCLUSIONS: This study demonstrated that the GIS thresholds used for ovarian cancer may also be appropriate for TNBC, but not ER + BC. GIS thresholds in TNBC were validated using clinical response data to platinum therapy.

Clinical Behavior, Management, and Treatment Response of Estrogen Receptor Low (1-10%) Breast Cancer.

INTRODUCTION: Estrogen receptor (ER) and progesterone receptor (PR) guide management and impact outcomes of breast cancer (BC). This study compares ER-low (1-10%) with ER-negative (< 1%) and ER-positive (>10%) BC and investigates the significance of PR expression within ER-low disease. PATIENTS AND METHODS: All patients with HER2-negative invasive BC were identified from the National Cancer Database 2018-2019. Treatment and outcomes were compared using chi-squared tests and multivariable logistic regression. RESULTS: Of 232,762 patients, ER expression was: negative (13.8%), low (2.0%), and > 10% (84.2%). Chemotherapy was given in 83.9% of ER- disease, 82.4% of ER-low/PR- disease, 58.9% of ER-low/PR+ disease, and only in 22.9% of ER+ disease. Within the ER-low subgroup, adjuvant endocrine therapy, recurrence score, and Ki67 varied by PR status (all < 0.01). Patients with ER-low disease selected for neoadjuvant chemotherapy (NAC) were younger and had higher T and N category, tumor grade, and Ki67. With NAC, pathological complete response (pCR) rates were similar between ER-low/PR- and ER-low/PR+ (39.5% and 38.1%, respectively, p = 0.67), and were closer to the ER- group (39.7%) than the ER+ group (8.4%). On multivariable analysis, the adjusted effect of ER status (1-10% versus > 10%) on chemotherapy administration was odds ratio (OR) 8.2 (95% CI 7.3-9.2, p < 0.001) for PR-negative, and OR 3.3 (95% CI 7.3-9.2, p < 0.001) for PR-positive. CONCLUSIONS: This study suggests that the tumor features and clinical management of ER-low tumors vary significantly by PR expression. Within ER-low tumors, PR- tumors more closely resemble ER- BC, while PR+ tumors exhibit less aggressive characteristics. In ER-low disease selected for treatment with NAC, response is similar to ER- regardless of PR status.

Alternating 17ß-Estradiol and Aromatase Inhibitor Therapies Is Efficacious in Postmenopausal Women with Advanced Endocrine-Resistant ER+ Breast Cancer.

PURPOSE: Strategies to implement estrogen therapy for advanced estrogen receptor-positive (ER+) breast cancer are underdeveloped. Preclinical data suggest that cycling treatment with 17ß-estradiol followed by estrogen deprivation can control tumor growth long-term. PATIENTS AND METHODS: Postmenopausal women with advanced ER+/HER2- breast cancer with recurrence or progression on ≥ 1 antiestrogen or aromatase inhibitor (AI)-based therapy were eligible. Patients received 17ß-estradiol (2 mg orally, three times a day) for 8 weeks followed by AI (physician's choice) for 16 weeks, alternating treatments on an 8-week/16-week schedule until disease progression. Patients then optionally received continuous single-agent treatment until a second instance of disease progression. Endpoints included 24-week clinical benefit and objective response per RECIST, and tumor genetic alterations. RESULTS: Of 19 evaluable patients, clinical benefit rate was 42.1% [95% confidence interval (CI), 23.1%-63.9%] and objective response rate (ORR) was 15.8% (95% CI, 5.7%-37.9%). One patient experienced a grade 3 adverse event related to 17ß-estradiol. Among patients who received continuous single-agent treatment until a second instance of disease progression, clinical benefit was observed in 5 of 12 (41.7%) cases. Tumor ER (ESR1) mutations were found by whole-exome profiling in 4 of 7 (57.1%) versus 2 of 9 (22.2%) patients who did versus did not experience clinical benefit from alternating 17ß-estradiol/AI therapy. The only two patients to experience objective responses to initial 17ß-estradiol had tumor ESR1 mutations. CONCLUSIONS: Alternating 17ß-estradiol/AI therapy may be a promising treatment for endocrine-refractory ER+ breast cancer, including following progression on CDK4/6 inhibitors or everolimus. Further study is warranted to determine whether the antitumor activity of 17ß-estradiol differs according to ESR1 mutation status.

NCCN Guidelines® Insights: Breast Cancer, Version 4.2023.

The NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines) for Breast Cancer address all aspects of management for breast cancer. The treatment landscape of metastatic breast cancer is evolving constantly. The therapeutic strategy takes into consideration tumor biology, biomarkers, and other clinical factors. Due to the growing number of treatment options, if one option fails, there is usually another line of therapy available, providing meaningful improvements in survival. This NCCN Guidelines Insights report focuses on recent updates specific to systemic therapy recommendations for patients with stage IV (M1) disease.

A Multiparameter Molecular Classifier to Predict Response to Neoadjuvant Lapatinib plus Trastuzumab without Chemotherapy in HER2+ Breast Cancer.

PURPOSE: Clinical trials reported 25% to 30% pathologic complete response (pCR) rates in HER2+ patients with breast cancer treated with anti-HER2 therapies without chemotherapy. We hypothesize that a multiparameter classifier can identify patients with HER2-"addicted" tumors who may benefit from a chemotherapy-sparing strategy. EXPERIMENTAL DESIGN: Baseline HER2+ breast cancer specimens from the TBCRC023 and PAMELA trials, which included neoadjuvant treatment with lapatinib and trastuzumab, were used. In the case of estrogen receptor-positive (ER+) tumors, endocrine therapy was also administered. HER2 protein and gene amplification (ratio), HER2-enriched (HER2-E), and PIK3CA mutation status were assessed by dual gene protein assay (GPA), research-based PAM50, and targeted DNA-sequencing. GPA cutoffs and classifier of response were constructed in TBCRC023 using a decision tree algorithm, then validated in PAMELA. RESULTS: In TBCRC023, 72 breast cancer specimens had GPA, PAM50, and sequencing data, of which 15 had pCR. Recursive partitioning identified cutoffs of HER2 ratio ≥ 4.6 and %3+ IHC staining ≥ 97.5%. With PAM50 and sequencing data, the model added HER2-E and PIK3CA wild-type (WT). For clinical implementation, the classifier was locked as HER2 ratio ≥ 4.5, %3+ IHC staining ≥ 90%, and PIK3CA-WT and HER2-E, yielding 55% and 94% positive (PPV) and negative (NPV) predictive values, respectively. Independent validation using 44 PAMELA cases with all three biomarkers yielded 47% PPV and 82% NPV. Importantly, our classifier's high NPV signifies its strength in accurately identifying patients who may not be good candidates for treatment deescalation. CONCLUSIONS: Our multiparameter classifier differentially identifies patients who may benefit from HER2-targeted therapy alone from those who need chemotherapy and predicts pCR to anti-HER2 therapy alone comparable with chemotherapy plus dual anti-HER2 therapy in unselected patients.

Advances in systemic therapies for triple negative breast cancer.

Triple negative breast cancer (TNBC) continues to be the subtype of breast cancer with the highest rates of recurrence and mortality. The lack of expression of targetable proteins such as the estrogen receptor and absence of HER2 amplification have made relying on cytotoxic chemotherapy necessary for decades. In the operable setting, efforts to improve outcomes have focused on escalation of systemic therapy and a shift toward preoperative delivery followed by a response adapted approach to postoperative systemic therapy. An improved understanding of tumor biology has resulted in the identification of subsets of patients with specific molecular features, leading to testing and approval of multiple new targeted therapies for this disease. Furthermore, advances in drug development have led to the approval of antibody-drug conjugates that are redefining classification schemes for breast cancer. This review focuses on the modern management of TNBC, with particular focus on recent updates in the treatment of operable disease, and an overview of the most recent promising advances in the therapeutic landscape of metastatic disease. It discusses the practical challenges and unanswered questions resulting from the approval of neoadjuvant immunotherapy and shares an approach in the clinic on topics for which evidence is lacking. In addition, it provides a glimpse into the future, highlighting challenges and opportunities for biomarker based right-sizing of preoperative therapy, refining evaluation of response to preoperative therapy after surgery, early diagnosis and detection of relapse, and areas of needed research for metastatic TNBC.

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

BACKGROUND: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype. Patients with TNBC are primarily treated with neoadjuvant chemotherapy (NAC). The response to NAC is prognostic, with reductions in overall survival and disease-free survival rates in those patients who do not achieve a pathological complete response (pCR). Based on this premise, we hypothesized that paired analysis of primary and residual TNBC tumors following NAC could identify unique biomarkers associated with post-NAC recurrence. METHODS AND RESULTS: We investigated 24 samples from 12 non-LAR TNBC patients with paired pre- and post-NAC data, including four patients with recurrence shortly after surgery (< 24 months) and eight who remained recurrence-free (> 48 months). These tumors were collected from a prospective NAC breast cancer study (BEAUTY) conducted at the Mayo Clinic. Differential expression analysis of pre-NAC biopsies showed minimal gene expression differences between early recurrent and nonrecurrent TNBC tumors; however, post-NAC samples demonstrated significant alterations in expression patterns in response to intervention. Topological-level differences associated with early recurrence were implicated in 251 gene sets, and an independent assessment of microarray gene expression data from the 9 paired non-LAR samples available in the NAC I-SPY1 trial confirmed 56 gene sets. Within these 56 gene sets, 113 genes were observed to be differentially expressed in the I-SPY1 and BEAUTY post-NAC studies. An independent (n = 392) breast cancer dataset with relapse-free survival (RFS) data was used to refine our gene list to a 17-gene signature. A threefold cross-validation analysis of the gene signature with the combined BEAUTY and I-SPY1 data yielded an average AUC of 0.88 for six machine-learning models. Due to the limited number of studies with pre- and post-NAC TNBC tumor data, further validation of the signature is needed. CONCLUSION: Analysis of multiomics data from post-NAC TNBC chemoresistant tumors showed down regulation of mismatch repair and tubulin pathways. Additionally, we identified a 17-gene signature in TNBC associated with post-NAC recurrence enriched with down-regulated immune genes.