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Abstract After disease progression on endocrine therapy (ET) plus a CDK4/6 inhibitor, there is no standardized sequence for subsequent treatment lines for estrogen receptor positive (ER+) metastatic breast cancer (MBC). CDK4/6i retrial as a treatment strategy is commonplace in modern clinical practice; however, the available prospective data investigating this strategy have had inconclusive results. To frame this data in a real-world context, we performed a retrospective analysis assessing the efficacy of CDK4/6is in 195 patients who had previous exposure to CDK4/6i in a prior treatment line at our institution. Among patients who had stopped a CDK4/6i due to toxicity, CDK4/6i retrial either immediately after with a different CDK4/6i or in a further treatment line with the same initial CDK4/6i was both safe and effective, with a median time to treatment failure (TTF) of 10.1 months (95%CI, 4.8–16.9). For patients whose disease progressed on a prior CDK4/6i, we demonstrated comparable median TTFs for patients rechallenged with the same CDK4/6i (4.3 months, 95%CI 3.2–5.5) and with a different CDK4/6i (4.7 months, 95%CI 3.7–6.0) when compared to the recent PACE, PALMIRA, and MAINTAIN trials. Exploratory genomic analysis suggested that the presence of mutations known to confer CDK4/6i resistance, such as TP53 mutations, CDK4 amplifications, and RB1 or FAT1 loss of function mutations may be molecular biomarkers predictive of CDK4/6i retrial failure.

Abstract Consensus guidelines recommend use of granulocyte colony stimulating factor in patients deemed at risk of chemotherapy‐induced neutropenia, however, these risk models are limited in the factors they consider and miss some cases of neutropenia. Clinical decision making could be supported using models that better tailor their predictions to the individual patient using the wealth of data available in electronic health records (EHRs). Here, we present a hybrid pharmacokinetic/pharmacodynamic (PKPD)/machine learning (ML) approach that uses predictions and individual Bayesian parameter estimates from a PKPD model to enrich an ML model built on her data. We demonstrate this approach using models developed on a large real‐world data set of 9121 patients treated for lymphoma, breast, or thoracic cancer. We also investigate the benefits of augmenting the training data using synthetic data simulated with the PKPD model. We find that PKPD‐enrichment of ML models improves prediction of grade 3–4 neutropenia, as measured by higher precision (61%) and recall (39%) compared to PKPD model predictions (47%, 33%) or base ML model predictions (51%, 31%). PKPD augmentation of ML models showed minor improvements in recall (44%) but not precision (56%), and data augmentation required careful tuning to control overfitting its predictions to the PKPD model. PKPD enrichment of ML shows promise for leveraging both the physiology‐informed predictions of PKPD and the ability of ML to learn predictor‐outcome relationships from large data sets to predict patient response to drugs in a clinical precision dosing context.

Abstract Up to 50% of patients with non-small cell lung cancer (NSCLC) develop brain metastasis (BM), yet the study of BM genomics has been limited by tissue access, incomplete clinical data, and a lack of comparison with paired extracranial specimens. Here we report a cohort of 233 patients with resected and sequenced (MSK-IMPACT) NSCLC BM and comprehensive clinical data. With matched samples (47 primary tumor, 42 extracranial metastatic), we show CDKN2A/B deletions and cell cycle pathway alterations to be enriched in the BM samples. Meaningful clinico-genomic correlations are noted, namely EGFR alterations in leptomeningeal disease (LMD) and MYC amplifications in multifocal regional brain progression. Patients who developed early LMD frequently have had uncommon, multiple, and persistently detectable EGFR driver mutations. The distinct mutational patterns identified in BM specimens compared to other tissue sites suggest specific biologic underpinnings of intracranial progression.

Summary: 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.

Background: Limited information is available for patients with breast cancer (BC) and coronavirus disease 2019 (COVID-19), especially among underrepresented racial/ethnic populations. Methods: This 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. Results: 1383 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. Conclusions: Using 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. Funding: This 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 number: CCC19 registry is registered on ClinicalTrials.gov, NCT04354701.

BackgroundSensitive and reliable biomarkers for early detection of recurrence are needed to improve post-definitive radiation risk stratification, disease management, and outcomes for patients with unresectable early-stage or locally advanced non-small cell lung cancer (NSCLC) who are treated with definitive radiation therapy (RT). This prospective, multistate single-center, cohort study investigated the association of circulating tumor DNA (ctDNA) status with recurrence in patients with unresectable stage I-III NSCLC who underwent definitive RT.MethodsA total of 70 serial plasma samples from 17 NSCLC patients were collected before, during, and after treatment. A personalized, tumor-informed ctDNA assay was used to track a set of up to 16 somatic, single nucleotide variants in the associated patient’s plasma samples.ResultsPre-treatment ctDNA detection rate was 82% (14/17) and varied based on histology and stage. ctDNA was detected in 35% (6/17) of patients at the first post-RT timepoint (median of 1.66 months following the completion of RT), all of whom subsequently developed clinical progression. At this first post-RT time point, patients with ctDNA-positivity had significantly worse progression-free survival (PFS) [hazard ratio (HR): 24.2, p=0.004], and ctDNA-positivity was the only significant prognostic factor associated with PFS (HR: 13.4, p=0.02) in a multivariate analysis. All patients who developed clinical recurrence had detectable ctDNA with an average lead time over radiographic progression of 5.4 months, and post-RT ctDNA positivity was significantly associated with poor PFS (p

Background: Data regarding outcomes among patients with cancer and co-morbid cardiovascular disease (CVD)/cardiovascular risk factors (CVRF) after SARS-CoV-2 infection are limited. Objectives: To compare Coronavirus disease 2019 (COVID-19) related complications among cancer patients with and without co-morbid CVD/CVRF. Methods: Retrospective cohort study of patients with cancer and laboratory-confirmed SARS-CoV-2, reported to the COVID-19 and Cancer Consortium (CCC19) registry from 03/17/2020 to 12/31/2021. CVD/CVRF was defined as established CVD or no established CVD, male ≥ 55 or female ≥ 60 years, and one additional CVRF. The primary endpoint was an ordinal COVID-19 severity outcome including need for hospitalization, supplemental oxygen, intensive care unit (ICU), mechanical ventilation, ICU or mechanical ventilation plus vasopressors, and death. Secondary endpoints included incident adverse CV events. Ordinal logistic regression models estimated associations of CVD/CVRF with COVID-19 severity. Effect modification by recent cancer therapy was evaluated. Results: Among 10,876 SARS-CoV-2 infected patients with cancer (median age 65 [IQR 54–74] years, 53% female, 52% White), 6253 patients (57%) had co-morbid CVD/CVRF. Co-morbid CVD/CVRF was associated with higher COVID-19 severity (adjusted OR: 1.25 [95% CI 1.11–1.40]). Adverse CV events were significantly higher in patients with CVD/CVRF (all p

Abstract Breast adenoid cystic carcinoma (AdCC) is a rare subtype of triple negative breast cancer. Two morphologic variants are described, namely classic AdCC (C-AdCC) and solid basaloid (SB-AdCC). Recent studies have shown that the SB-AdCC variant has significantly worse prognosis than C-AdCC. Due to the rarity of SB-AdCC, no standard recommendations are available for its management. Data on the use and benefit of chemotherapy in patients with SB-AdCC are sparse and the response to neoadjuvant chemotherapy has not been reported. We present the clinical and pathologic findings of a patient with SB-AdCC treated with neoadjuvant chemotherapy who achieved a remarkable pathologic response.

Abstract The addition of pertuzumab (P) to trastuzumab (H) and neoadjuvant chemotherapy (NAC) has decreased the risk of distant recurrence in early stage HER2-positive breast cancer. The incidence of brain metastases (BM) in patients who achieved pathological complete response (pCR) versus those who do not is unknown. In this study, we sought the incidence of BM in patients receiving HP-containing NAC as well as survival outcome. We reviewed the medical records of 526 early stage HER2-positive patients treated with an HP-based regimen at Memorial Sloan Kettering Cancer Center (MSKCC), between September 1, 2013 to November 1, 2019. The primary endpoint was to estimate the cumulative incidence of BM in pCR versus non-pCR patients; secondary endpoints included disease free-survival (DFS) and overall survival (OS). After a median follow-up of 3.2 years, 7 out of 286 patients with pCR had a BM while 5 out of 240 non-pCR patients had a BM. The 3-year DFS was significantly higher in the pCR group compared to non-pCR group (95% vs 91 %, p = 0.03) and the same trend was observed for overall survival. In our cohort, despite the better survival outcomes of patients who achieved pCR, we did not observe appreciable differences in the incidence of BM by pCR/non-pCR status. This finding suggests that the BM incidence could not be associated with pCR. Future trials with new small molecules able to cross the blood brain barrier should use more specific biomarkers rather than pCR for patients’ selection.

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.

Liquid biopsies allow the non-invasive detection of somatic mutations from tumours. Here, the authors develop and test MSK-ACCESS, an NGS-based clinical assay for identifying low frequency mutations in 129 genes and describe how it benefits patients in the clinic.

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 Background Cell-free DNA (cfDNA) profiling is increasingly used to guide cancer care, yet mutations are not always identified. The ability to detect somatic mutations in plasma depends on both assay sensitivity and the fraction of circulating DNA in plasma that is tumor-derived (i.e., cfDNA tumor fraction). We hypothesized that cfDNA tumor fraction could inform the interpretation of negative cfDNA results and guide the choice of subsequent assays of greater genomic breadth or depth. Methods Plasma samples collected from 118 metastatic cancer patients were analyzed with cf-IMPACT, a modified version of the FDA-authorized MSK-IMPACT tumor test that can detect genomic alterations in 410 cancer-associated genes. Shallow whole genome sequencing (sWGS) was also performed in the same samples to estimate cfDNA tumor fraction based on genome-wide copy number alterations using z-score statistics. Plasma samples with no somatic alterations detected by cf-IMPACT were triaged based on sWGS-estimated tumor fraction for analysis with either a less comprehensive but more sensitive assay (MSK-ACCESS) or broader whole exome sequencing (WES). Results cfDNA profiling using cf-IMPACT identified somatic mutations in 55/76 (72%) patients for whom MSK-IMPACT tumor profiling data were available. A significantly higher concordance of mutational profiles and tumor mutational burden (TMB) was observed between plasma and tumor profiling for plasma samples with a high tumor fraction (z-score≥5). In the 42 patients from whom tumor data was not available, cf-IMPACT identified mutations in 16/42 (38%). In total, cf-IMPACT analysis of plasma revealed mutations in 71/118 (60%) patients, with clinically actionable alterations identified in 30 (25%), including therapeutic targets of FDA-approved drugs. Of the 47 samples without alterations detected and low tumor fraction (z-score

Abstract Five to ten percent of ER+ metastatic breast cancer (MBC) tumors harbor somatic PTEN mutations. Loss of function of this tumor-suppressor gene defines a highly aggressive, treatment-refractory disease for which new therapies are urgently needed. This Phase I multipart expansion study assessed oral capivasertib with fulvestrant in patients with PTEN-mutant ER+ MBC. Safety and tolerability were assessed by standard methods. Plasma and tumor were collected for NGS and immunohistochemistry analyses of PTEN protein expression. In 31 eligible patients (12 fulvestrant naive; 19 fulvestrant pretreated), the 24-week clinical benefit rate was 17% in fulvestrant-naive and 42% in fulvestrant-pretreated patients, with objective response rate of 8% and 21%, respectively. Non-functional PTEN was centrally confirmed in all cases by NGS or immunohistochemistry. Co­mutations occurred in PIK3CA (32%), with less ESR1 (10% vs 72%) and more TP53 (40% vs 28%) alterations in fulvestrant-naive versus fulvestrant-pretreated patients, respectively. PTEN was clonally dominant in most patients. Treatment-related grade ≥3 adverse events occurred in 32% of patients, most frequently diarrhea and maculopapular rash (both n = 2). In this clinical study, which selectively targeted the aggressive PTEN-mutant ER+ MBC, capivasertib plus fulvestrant was tolerable and clinically active. Phenotypic and genomic differences were apparent between fulvestrant-naive and -pretreated patients. Trial registration number for the study is NCT01226316.

Abstract Metaplastic breast cancers (MBCs) are characterized by complex genomes, which seem to vary according to their histologic subtype. TERT promoter hotspot mutations and gene amplification are rare in common forms of breast cancer, but present in a subset of phyllodes tumors. Here, we sought to determine the frequency of genetic alterations affecting TERT in a cohort of 60 MBCs with distinct predominant metaplastic components (squamous, 23%; spindle, 27%; osseous, 8%; chondroid, 42%), and to compare the repertoire of genetic alterations of MBCs according to the presence of TERT promoter hotspot mutations or gene amplification. Forty-four MBCs were subjected to: whole-exome sequencing (WES; n = 27) or targeted sequencing of 341-468 cancer-related genes (n = 17); 16 MBCs were subjected to Sanger sequencing of the TERT promoter, TP53 and selected exons of PIK3CA, HRAS, and BRAF. TERT promoter hotspot mutations (n = 9) and TERT gene amplification (n = 1) were found in 10 of the 60 MBCs analyzed, respectively. These TERT alterations were less frequently found in MBCs with predominant chondroid differentiation than in other MBC subtypes (p = 0.01, Fisher’s exact test) and were mutually exclusive with TP53 mutations (p

Abstract Identification of actionable genomic vulnerabilities is key to precision oncology. Utilizing a large-scale drug screening in patient-derived xenografts, we uncover driver gene alteration connections, derive driver co-occurrence (DCO) networks, and relate these to drug sensitivity. Our collection of 53 drug-response predictors attains an average balanced accuracy of 58% in a cross-validation setting, rising to 66% for a subset of high-confidence predictions. We experimentally validated 12 out of 14 predictions in mice and adapted our strategy to obtain drug-response models from patients’ progression-free survival data. Our strategy reveals links between oncogenic alterations, increasing the clinical impact of genomic profiling.

Abstract 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.

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.

The purpose of this cross-sectional study on 191 HIV/AIDS patient was to prepare the first Persian translation of complete WHOQOL-HIV instrument, evaluate its reliability and validity, and apply it to determine quality of life and its associated factors in Tehran, Iran. Student's t-test was used to compare quality of life between groups. Mean Cronbach’s α of facets in all six domains of instrument were more than 0.6 indicating good reliability. Item/total corrected correlations coefficients had a lower limit of more than 0.5 in all facets except for association between energy and fatigue facet and physical domain. Compared to younger participants, patients older than 35 years had significantly lower scores in overall quality of life (P = 0.003), social relationships (P = 0.021), and spirituality/religion/personal beliefs (P = 0.024). Unemployed patients had significantly lower scores in overall quality of life (P = 0.01), level of independence (P = 0.004), and environment (P = 0.001) compared to employed participants. This study demonstrated that the standard, complete WHOQOL-HIV 120 instrument translated into Farsi and evaluated among Iranian participants provides a reliable and valid basis for future research on quality of life for HIV and other patients in Iran.

Abstract: The performances of the junctionless nanowire transistor (JNT) are evaluated under high-performance (HP) ITRS device technical requirements for the 25nm technology node. The electrical characteristics of the devices are obtained from numerical simulations. The threshold voltage of JNT can be easily adjusted by changing different variable parameters such as fin width, fin thickness, doping concentration, gate oxide thickness and gate work function. The variation of threshold voltage with physical parameters is analyzed. The current drive is controlled by doping concentration and nanowire size. For gate length down to 25nm, a 30–40% increase in drain current is also reported by using a fin aspect ratio of 2 instead of 1. Additional source and drain implantation can be applied to improve the current drive. [Copyright &y& Elsevier]