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BackgroundLimited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations.MethodsThis is a COVID-19 and Cancer Consortium (CCC19) registry-based retrospective cohort study of females with active or history of BC and laboratory-confirmed severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection diagnosed between March 2020 and June 2021 in the US. Primary outcome was COVID-19 severity measured on a five-level ordinal scale, including none of the following complications, hospitalization, intensive care unit admission, mechanical ventilation, and all-cause mortality. Multivariable ordinal logistic regression model identified characteristics associated with COVID-19 severity.Results1383 female patient records with BC and COVID-19 were included in the analysis, the median age was 61 years, and median follow-up was 90 days. Multivariable analysis revealed higher odds of COVID-19 severity for older age (aOR per decade, 1.48 [95% CI, 1.32-1.67]); Black patients (aOR 1.74; 95 CI 1.24-2.45), Asian Americans and Pacific Islander patients (aOR 3.40; 95 CI 1.70-6.79) and Other (aOR 2.97; 95 CI 1.71-5.17) racial/ethnic groups; worse ECOG performance status (ECOG PS ≥2: aOR, 7.78 [95% CI, 4.83-12.5]); pre-existing cardiovascular (aOR, 2.26 [95% CI, 1.63-3.15])/pulmonary comorbidities (aOR, 1.65 [95% CI, 1.20-2.29]); diabetes mellitus (aOR, 2.25 [95% CI, 1.66-3.04]); and active and progressing cancer (aOR, 12.5 [95% CI, 6.89-22.6]). Hispanic ethnicity, timing, and type of anti-cancer therapy modalities were not significantly associated with worse COVID-19 outcomes. The total all-cause mortality and hospitalization rate for the entire cohort was 9% and 37%, respectively however, it varied according to the BC disease status.ConclusionsUsing one of the largest registries on cancer and COVID-19, we identified patient and BC-related factors associated with worse COVID-19 outcomes. After adjusting for baseline characteristics, underrepresented racial/ethnic patients experienced worse outcomes compared to non-Hispanic White patients.FundingThis study was partly supported by National Cancer Institute grant number P30 CA068485 to Tianyi Sun, Sanjay Mishra, Benjamin French, Jeremy L Warner; P30-CA046592 to Christopher R Friese; P30 CA023100 for Rana R McKay; P30-CA054174 for Pankil K Shah and Dimpy P Shah; KL2 TR002646 for Pankil Shah and the American Cancer Society and Hope Foundation for Cancer Research (MRSG-16-152-01-CCE) and P30-CA054174 for Dimpy P Shah. REDCap is developed and supported by Vanderbilt Institute for Clinical and Translational Research grant support (UL1 TR000445 from NCATS/NIH). The funding sources had no role in the writing of the manuscript or the decision to submit it for publication.Clinical trial numberCCC19 registry is registered on ClinicalTrials.gov, NCT04354701.

PurposeLynch syndrome is defined by germline pathogenic mutations involving DNA mismatch repair (MMR) genes and linked with the development of MMR-deficient colon and endometrial cancers. Whether breast cancers developing in the context of Lynch syndrome are causally related to MMR deficiency (MMRd), remains controversial. Thus, we explored the morphologic and genomic characteristics of breast cancers occurring in Lynch syndrome individuals.Experimental designA retrospective analysis of 20,110 patients with cancer who underwent multigene panel genetic testing was performed to identify individuals with a likely pathogenic/pathogenic germline variant in MLH1, MSH2, MSH6, or PMS2 who developed breast cancers. The histologic characteristics and IHC assessment of breast cancers for MMR proteins and programmed death-ligand 1 (PD-L1) expression were assessed on cases with available materials. DNA samples from paired tumors and blood were sequenced with Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (≥468 key cancer genes). Microsatellite instability (MSI) status was assessed utilizing MSISensor. Mutational signatures were defined using SigMA.ResultsA total of 272 individuals with Lynch syndrome were identified, 13 (5%) of whom had primary breast cancers. The majority of breast cancers (92%) were hormone receptor-positive tumors. Five (42%) of 12 breast cancers displayed loss of MMR proteins by IHC. Four (36%) of 11 breast cancers subjected to tumor-normal sequencing showed dominant MSI mutational signatures, high tumor mutational burden, and indeterminate (27%) or high MSISensor scores (9%). One patient with metastatic MMRd breast cancer received anti-PD1 therapy and achieved a robust and durable response.ConclusionsA subset of breast cancers developing in individuals with Lynch syndrome are etiologically linked to MMRd and may benefit from anti-PD1/PD-L1 immunotherapy.

BACKGROUND: For breast cancer patients undergoing neoadjuvant chemotherapy (NAC), pathologic complete response (pCR; no invasive or in situ) cannot be assessed non-invasively so all patients undergo surgery. The aim of our study was to develop and validate a radiomics classifier that classifies breast cancer pCR post-NAC on MRI prior to surgery. METHODS: This retrospective study included women treated with NAC for breast cancer from 2014 to 2016 with (1) pre- and post-NAC breast MRI and (2) post-NAC surgical pathology report assessing response. Automated radiomics analysis of pre- and post-NAC breast MRI involved image segmentation, radiomics feature extraction, feature pre-filtering, and classifier building through recursive feature elimination random forest (RFE-RF) machine learning. The RFE-RF classifier was trained with nested five-fold cross-validation using (a) radiomics only (model 1) and (b) radiomics and molecular subtype (model 2). Class imbalance was addressed using the synthetic minority oversampling technique. RESULTS: Two hundred seventy-three women with 278 invasive breast cancers were included; the training set consisted of 222 cancers (61 pCR, 161 no-pCR; mean age 51.8 years, SD 11.8), and the independent test set consisted of 56 cancers (13 pCR, 43 no-pCR; mean age 51.3 years, SD 11.8). There was no significant difference in pCR or molecular subtype between the training and test sets. Model 1 achieved a cross-validation AUROC of 0.72 (95% CI 0.64, 0.79) and a similarly accurate (P = 0.1) AUROC of 0.83 (95% CI 0.71, 0.94) in both the training and test sets. Model 2 achieved a cross-validation AUROC of 0.80 (95% CI 0.72, 0.87) and a similar (P = 0.9) AUROC of 0.78 (95% CI 0.62, 0.94) in both the training and test sets. CONCLUSIONS: This study validated a radiomics classifier combining radiomics with molecular subtypes that accurately classifies pCR on MRI post-NAC.

Endocrine therapy (ET) is a pivotal strategy to manage early- and advanced-stage estrogen receptor-positive (ER+) breast cancer. In patients with metastatic breast cancer (MBC), progression of disease inevitably occurs due to the presence of acquired or intrinsic resistance mechanisms. ET resistance can be driven by ligand-independent, ER-mediated signaling that promotes tumor proliferation in the absence of hormone, or ER-independent oncogenic signaling that circumvents endocrine regulated transcription pathways. Estrogen receptor 1 (ESR1) mutations induce constitutive ER activity and upregulate ER-dependent gene transcription, provoking resistance to estrogen deprivation and aromatase inhibitor therapy. The role ESR1 mutations play in regulating response to other therapies, such as the selective estrogen receptor degrader (SERD) fulvestrant and the available CDK4/6 inhibitors, is less clear. Novel oral SERDs and other next-generation ETs are in clinical development for ER+ breast cancer as single agents and in combination with established targeted therapies. Recent results from the phase III EMERALD trial demonstrated improved outcomes with the oral SERD elacestrant compared to standard anti-estrogen therapies in ER+ MBC after prior progression on ET, and other agents have shown promise in both the laboratory and early-phase clinical trials. In this review, we will discuss the emerging data related to oral SERDs and other novel ET in managing ER+ breast cancer. As clinical data continue to mature on these next-generation ETs, important questions will emerge related to the optimal sequence of therapeutic options and the genomic and molecular landscape of resistance to these agents. [ABSTRACT FROM AUTHOR]

Inhibition of HER2 in HER2-amplified breast cancer has been remarkably successful clinically, as demonstrated by the efficacy of HER-kinase inhibitors and HER2-antibody treatments. Whilst resistance to HER2 inhibition is common in the metastatic setting, the specific programs downstream of HER2 driving resistance are not established. Through genomic profiling of 733 HER2-amplified breast cancers, we identify enrichment of somatic alterations that promote MEK/ERK signaling in metastatic tumors with shortened progression-free survival on anti-HER2 therapy. These mutations, including NF1 loss and ERBB2 activating mutations, are sufficient to mediate resistance to FDA-approved HER2 kinase inhibitors including tucatinib and neratinib. Moreover, resistant tumors lose AKT dependence while undergoing a dramatic sensitization to MEK/ERK inhibition. Mechanistically, this driver pathway switch is a result of MEK-dependent activation of CDK2 kinase. These results establish genetic activation of MAPK as a recurrent mechanism of anti-HER2 therapy resistance that may be effectively combated with MEK/ERK inhibitors. Resistance to HER2 inhibition in HER2- amplified breast cancer is common in the metastatic setting and the underlying molecular mechanisms remain unknown. Here, the authors, perform genomic profiling of 733 HER2-amplified breast cancers and propose genetic activation of MAPK as a resistance mechanism. [ABSTRACT FROM AUTHOR]

Activating mutations in PIK3CA are frequently found in estrogen-receptor-positive (ER+) breast cancer, and the combination of the phosphatidylinositol 3-kinase (PI3K) inhibitor alpelisib with anti-ER inhibitors is approved for therapy. We have previously demonstrated that the PI3K pathway regulates ER activity through phosphorylation of the chromatin modifier KMT2D. Here, we discovered a methylation site on KMT2D, at K1330 directly adjacent to S1331, catalyzed by the lysine methyltransferase SMYD2. SMYD2 loss attenuates alpelisib-induced KMT2D chromatin binding and alpelisib-mediated changes in gene expression, including ER-dependent transcription. Knockdown or pharmacological inhibition of SMYD2 sensitizes breast cancer cells, patient-derived organoids, and tumors to PI3K/AKT inhibition and endocrine therapy in part through KMT2D K1330 methylation. Together, our findings uncover a regulatory crosstalk between post-translational modifications that fine-tunes KMT2D function at the chromatin. This provides a rationale for the use of SMYD2 inhibitors in combination with PI3Kα/AKT inhibitors in the treatment of ER+/ PIK3CA mutant breast cancer. [Display omitted] • KMT2D is methylated at K1330 by SMYD2 • There is crosstalk between phosphorylation of KMT2D at S1331 and methylation at K1330 • Loss of SMYD2 abrogates PI3Ki-induced KMT2D chromatin binding and ER-dependent transcription • Inhibition of KMT2D methylation sensitizes cells and tumors to PI3K/AKT inhibition Blawski et al. show that KMT2D is methylated by the lysine methyltransferase SMYD2 at K1330. SMYD2 loss attenuates PI3K inhibitor-induced KMT2D chromatin binding at estrogen-receptor (ER) loci and ER-dependent transcription. SMYD2 inhibition sensitizes cells, patient-derived organoids, and tumors to PI3K/AKT inhibition and endocrine therapy through KMT2D K1330 methylation. [ABSTRACT FROM AUTHOR]

PURPOSE: Key oncology end points are not routinely encoded into electronic medical records (EMRs). We assessed whether natural language processing (NLP) can abstract treatment discontinuation rationale from unstructured EMR notes to estimate toxicity incidence and progression-free survival (PFS). METHODS: We constructed a retrospective cohort of 6,115 patients with early-stage and 701 patients with metastatic breast cancer initiating care at Memorial Sloan Kettering Cancer Center from 2008 to 2019. Each cohort was divided into training (70%), validation (15%), and test (15%) subsets. Human abstractors identified the clinical rationale associated with treatment discontinuation events. Concatenated EMR notes were used to train high-dimensional logistic regression and convolutional neural network models. Kaplan-Meier analyses were used to compare toxicity incidence and PFS estimated by our NLP models to estimates generated by manual labeling and time-to-treatment discontinuation (TTD). RESULTS: Our best high-dimensional logistic regression models identified toxicity events in early-stage patients with an area under the curve of the receiver-operator characteristic of 0.857 ± 0.014 (standard deviation) and progression events in metastatic patients with an area under the curve of 0.752 ± 0.027 (standard deviation). NLP-extracted toxicity incidence and PFS curves were not significantly different from manually extracted curves (P =.95 and P =.67, respectively). By contrast, TTD overestimated toxicity in early-stage patients (P <.001) and underestimated PFS in metastatic patients (P <.001). Additionally, we tested an extrapolation approach in which 20% of the metastatic cohort were labeled manually, and NLP algorithms were used to abstract the remaining 80%. This extrapolated outcomes approach resolved PFS differences between receptor subtypes (P <.001 for hormone receptor+/human epidermal growth factor receptor 2− v human epidermal growth factor receptor 2+ v triple-negative) that could not be resolved with TTD. CONCLUSION: NLP models are capable of abstracting treatment discontinuation rationale with minimal manual labeling. [ABSTRACT FROM AUTHOR]

Aims: The American Society of Clinical Oncology/College of American Pathologists (ASCO/CAP) updated the testing guideline in 2018 to address issues arising from uncommon human epidermal growth factor receptor 2 (HER2) fluorescence in‐situ hybridisation (FISH) results according to the 2013 guideline. Next‐generation sequencing (NGS) may be used to better classify patients. The aim of this study was to assess the ERBB2 amplification status of invasive breast carcinoma with equivocal HER2 immunohistochemistry (IHC) results by using NGS, focusing on Group 4 (HER2/CEP17 ratio of <2.0; average HER2 signals/cell of ≥4.0 and <6.0). Methods and results: We retrospectively reviewed HER2 FISH and NGS data of HER2 IHC‐equivocal breast carcinomas at our centre between January 2009 and September 2019, wherein all three assays were performed on the same tissue block, and compared HER2 FISH results, according to the 2018 ASCO/CAP guideline, and the ERBB2 amplification status determined with NGS. A total of 52 HER2 FISH and NGS results from 51 patients with HER2 IHC‐equivocal breast carcinomas were reviewed. The cohort included eight cases classified as 2018 ASCO/CAP in‐situ hybridisation Group 1, three classified as Group 2, three classified as Group 3, 14 classified as Group 4, and 24 classified as Group 5. Thirteen of 14 (92.9%) Group 4 (HER2‐negative) cases were classified as ERBB2‐non‐amplified by the use of NGS; the discordant case was later classified as Group 1 with alternative sample FISH testing. NGS revealed no significant difference in somatic mutations or copy number alterations between Groups 4 and 5. Conclusions: Our NGS findings support the reclassification of HER2 FISH‐equivocal cases as HER2‐negative under the 2018 ASCO/CAP guideline. [ABSTRACT FROM AUTHOR]

Activating mutations in PIK3CA are frequent in human breast cancer, and phosphoinositide 3-kinase alpha (PI3Ka) inhibitors have been approved for therapy. To characterize determinants of sensitivity to these agents, we analyzed PIK3CA-mutant cancer genomes and observed the presence of multiple PIK3CA mutations in 12 to 15% of breast cancers and other tumor types, most of which (95%) are double mutations. Double PIK3CA mutations are in cis on the same allele and result in increased PI3K activity, enhanced downstream signaling, increased cell proliferation, and tumor growth. The biochemical mechanisms of dual mutations include increased disruption of p110a binding to the inhibitory subunit p85a, which relieves its catalytic inhibition, and increased p110a membrane lipid binding. Double PIK3CA mutations predict increased sensitivity to PI3Ka inhibitors compared with single-hotspot mutations. [ABSTRACT FROM AUTHOR]

Cyclin-dependent kinase 4 and 6 inhibitors (CDK4/6i) are key therapeutic agents in the management of metastatic hormone-receptor-positive breast cancer. However, the emergence of drug resistance limits their long-term efficacy. Here, we show that breast cancer cells develop CDK4/6i resistance via a sequential two-step process of E2F activation. This process entails retinoblastoma (Rb)-protein degradation, followed by c-Myc-mediated amplification of E2F transcriptional activity. CDK4/6i treatment halts cell proliferation in an Rb-dependent manner but dramatically reduces Rb-protein levels. However, this reduction in Rb levels insufficiently induces E2F activity. To develop CDK4/6i resistance, upregulation or activating mutations in mitogenic or hormone signaling are required to stabilize c-Myc levels, thereby augmenting E2F activity. Our analysis of pre-treatment tumor samples reveals a strong correlation between c-Myc levels, rather than Rb levels, and poor therapeutic outcomes after CDK4/6i treatment. Moreover, we propose that proteasome inhibitors can potentially reverse CDK4/6i resistance by restoring Rb levels. [Display omitted] • Breast cancer cells develop CDK4/6i resistance via sequential E2F activation • Rb-protein degradation and c-Myc-mediated amplification of E2F activity are key mechanisms • c-Myc levels, not Rb levels, predict poor outcomes after CDK4/6i treatment • Proteasome inhibitors restoring Rb levels can potentially overcome CDK4/6i resistance Kim et al. demonstrate that breast cancer cells develop resistance to CDK4/6 inhibitors through a two-step E2F activation process involving Rb-protein degradation and c-Myc-mediated amplification of E2F activity. They suggest that proteasome inhibitors, which restore Rb levels, could potentially overcome this resistance. [ABSTRACT FROM AUTHOR]

Introduction: Previous studies showed that higher testosterone levels are associated with greater risk of breast cancer in premenopausal women, but the literature is scant and inconsistent. Methods: In a prospective nested case-control study of 104 premenopausal women with incident breast cancer and 225 matched controls, all characterized by regular menstrual cycles throughout their lifetime, we measured the concentration of estradiol, total and free testosterone (FT), progesterone, sex hormone-binding globulin (SHBG), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) in blood samples collected on days 20 through 24 of their cycles. Results: In logistic regression models, the multivariate odds ratios (ORs) of invasive breast cancer for women in the highest tertile of circulating FT compared with the lowest was 2.43 (95% confidence interval (95% CI), 1.15 to 5.10; Ptrend = 0.03), whereas for total testosterone, the association had the same direction but was not statistically significant (OR, 1.27; 95% CI, 0.62 to 2.61; Ptrend = 0.51). Endogenous progesterone was not statistically associated with breast cancer (OR, 1.16; 95% CI, 0.60 to 2.27; Ptrend = 0.75), nor were the other considered hormones. Conclusions: Consistent with previous prospective studies in premenopausal women and our own earlier investigation, we observed that higher levels of FT are positively associated with breast cancer risk in women with regular menstrual cycles throughout their lifetimes. No evidence of risk was found associated with the other endogenous sex steroids. [ABSTRACT FROM AUTHOR]

Chromatin accessibility data can elucidate the developmental origin of cancer cells and reveal the enhancer landscape of key oncogenic transcriptional regulators. We develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to combine chromatin accessibility data with large tumor expression data and model the effect of enhancers on transcriptional programs in multiple cancers. We generate a new ATAC-seq data profiling chromatin accessibility in gynecologic and basal breast cancer cell lines and apply PSIONIC to 723 patient and 96 cell line RNA-seq profiles from ovarian, uterine, and basal breast cancers. Our computational framework enables us to share information across tumors to learn patient-specific TF activities, revealing regulatory differences between and within tumor types. PSIONIC-predicted activity for MTF1 in cell line models correlates with sensitivity to MTF1 inhibition, showing the potential of our approach for personalized therapy. Many identified TFs are significantly associated with survival outcome. To validate PSIONIC-derived prognostic TFs, we perform immunohistochemical analyses in 31 uterine serous tumors for ETV6 and 45 basal breast tumors for MITF and confirm that the corresponding protein expression patterns are also significantly associated with prognosis. Epigenomic data on chromatin accessibility and transcription factor occupancy can reveal enhancer landscapes in cancer. Here, the authors develop a computational strategy called PSIONIC (patient-specific inference of networks informed by chromatin) to model the impact of enhancers on transcriptional programs in gynecologic and basal breast cancers. [ABSTRACT FROM AUTHOR]

Purpose: Breast cancer diagnosis at a very young age has been independently correlated with worse outcomes. Appropriately intensifying treatment in these patients is warranted, even as we acknowledge the risks of potentially mutagenic adjuvant therapies. We examined local control, distant control, overall survival, and secondary malignancy rates by age cohort and by initial surgical strategy.Methods and Materials: Female patients less than or equal to 35 years of age diagnosed with invasive breast cancer from January 1, 1990, to December 31, 2010, were identified. Control groups of those aged 36 to 50 years (n = 6246) and 51 to 70 years (n = 7294) were delineated from an institutional registry. Clinicopathologic and follow-up information was collected. Chi-squared test was used to compare frequencies of categorical variables. Survival endpoints were evaluated using Kaplan-Meier methodology.Results: A total of 529 patients ≤35 years of age met criteria for analysis. The median age of diagnosis was 32 years (range 20-35). Median follow-up was 10.3 years. On multivariable analysis, factors associated with overall survival (OS) were tumor size (hazard ratio [HR] 1.14, P = .02), presence of lymphovascular invasion (HR 2.2, P <.001), estrogen receptor positivity (HR 0.64, P = .015), receipt of adjuvant chemotherapy (HR 0.52, P = .035), and black race (HR 2.87, P <.001). The ultra-young were more likely to experience local failure compared with the aged 36 to 50 group (HR 2.2, 95% CI 1.8-2.6, P < .001) and aged 51 to 70 group (HR 3.1, 95% CI 2.45 - 3.9, P <.001). The cumulative incidence of secondary malignancies at 5 and 10 years was 2.2% and 4.4%, respectively. Receipt of radiation was not significantly associated with secondary malignancies or contralateral breast cancer.Conclusion: Survival and recurrence outcomes in breast cancer patients ≤35 years are worse compared with those aged 36 to 50 or 51 to 70 years. Based on our data, breast conservation therapy is appropriate for these patients, and the concern for second malignancies should not impinge on the known indications for postoperative radiation therapy. [ABSTRACT FROM AUTHOR]

PIK3CA , encoding the PI3Kα isoform, is the most frequently mutated oncogene in estrogen receptor (ER)-positive breast cancer. Isoform-selective PI3K inhibitors are used clinically but intrinsic and acquired resistance limits their utility. Improved selection of patients that will benefit from these drugs requires predictive biomarkers. We show here that persistent FOXM1 expression following drug treatment is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer. FOXM1 drives expression of lactate dehydrogenase (LDH) but not hexokinase 2 (HK-II). The downstream metabolic changes can therefore be detected using MRI of LDH-catalyzed hyperpolarized 13C label exchange between pyruvate and lactate but not by positron emission tomography measurements of HK-II-mediated trapping of the glucose analog 2-deoxy-2-18F]fluorodeoxyglucose. Rapid assessment of treatment response in breast cancer using this imaging method could help identify patients that benefit from PI3Kα inhibition and design drug combinations to counteract the emergence of resistance. • Imaging hyperpolarized [1-13C]pyruvate metabolism detects response to PI3Kα inhibitors • PI3Kα inhibitors downregulate FOXM1 expression in ER+ breast tumor models • FOXM1 induces LDH expression and 13C label exchange between pyruvate and lactate • Imaging [1-13C]pyruvate metabolism could be used clinically to guide treatment Ros et al. find that imaging of hyperpolarized [1-13C]pyruvate metabolism allows early detection of response and resistance to PI3Kα inhibition in PIK3CA -mutant ER+ breast cancer, which could be used clinically to guide treatment. Increased expression of FOXM1 results in resistance to PI3Kα inhibition and sustains LDH expression. [ABSTRACT FROM AUTHOR]