Evaluation of markers of immunity in different metastatic immune microenvironments suggests more suppression within breast to liver metastases in breast cancer.

PURPOSE: Programmed death receptor ligand-1 (PD-L1) expression and tumor mutational burden (TMB) are approved screening biomarkers for immune checkpoint inhibition (ICI) in advanced triple negative breast cancer. We examined these biomarkers along with characterization of the tumor microenvironment (TME) between breast tumors (BrTs), axillary metastases (AxMs), liver metastases (LvMs), non-axillary lymph node metastases, and non-liver metastases to determine differences related to site of metastatic disease. METHODS: 3076 unpaired biopsies from breast cancer patients were analyzed using whole transcriptome sequencing and NextGen DNA depicting TMB within tumor sites. The PD-L1 positivity was determined with VENTANA PD-L1 (SP142) assay. The immune cell fraction within the TME was calculated by QuantiSeq and MCP-counter. RESULTS: Compared to BrT, more LvM samples had a high TMB (≥ 10 mutations/Mb) and fewer LvM samples had PD-L1+ expression. Evaluation of the TME revealed that LvM sites harbored lower infiltration of adaptive immune cells, such as CD4+, CD8+, and regulatory T-cells compared with the BrT foci. We saw differences in innate immune cell infiltration in LvM compared to BrT, including neutrophils and NK cells. CONCLUSIONS: LvMs are less likely to express PD-L1+ tumor cells but more likely to harbor high TMB as compared to BrTs. Unlike AxMs, LvMs represent a more immunosuppressed TME and demonstrate lower gene expression associated with adaptive immunity compared to BrTs. These findings suggest biopsy site be considered when interpreting results that influence ICI use for treatment and further investigation of immune composition and biomarkers expression by metastatic site.

Kinase Inhibitor Pulldown Assay Identifies a Chemotherapy Response Signature in Triple-negative Breast Cancer Based on Purine-binding Proteins.

Triple-negative breast cancer (TNBC) constitutes 10%-15% of all breast tumors. The current standard of care is multiagent chemotherapy, which is effective in only a subset of patients. The original objective of this study was to deploy a mass spectrometry (MS)-based kinase inhibitor pulldown assay (KIPA) to identify kinases elevated in non-pCR (pathologic complete response) cases for therapeutic targeting. Frozen optimal cutting temperature compound-embedded core needle biopsies were obtained from 43 patients with TNBC before docetaxel- and carboplatin-based neoadjuvant chemotherapy. KIPA was applied to the native tumor lysates that were extracted from samples with high tumor content. Seven percent of all identified proteins were kinases, and none were significantly associated with lack of pCR. However, among a large population of "off-target" purine-binding proteins (PBP) identified, seven were enriched in pCR-associated samples (P < 0.01). In orthogonal mRNA-based TNBC datasets, this seven-gene "PBP signature" was associated with chemotherapy sensitivity and favorable clinical outcomes. Functional annotation demonstrated IFN gamma response, nuclear import of DNA repair proteins, and cell death associations. Comparisons with standard tandem mass tagged-based discovery proteomics performed on the same samples demonstrated that KIPA-nominated pCR biomarkers were unique to the platform. KIPA is a novel biomarker discovery tool with unexpected utility for the identification of PBPs related to cytotoxic drug response. The PBP signature has the potential to contribute to clinical trials designed to either escalate or de-escalate therapy based on pCR probability. Significance: The identification of pretreatment predictive biomarkers for pCR in response to neoadjuvant chemotherapy would advance precision treatment for TNBC. To complement standard proteogenomic discovery profiling, a KIPA was deployed and unexpectedly identified a seven-member non-kinase PBP pCR-associated signature. Individual members served diverse pathways including IFN gamma response, nuclear import of DNA repair proteins, and cell death.

Genetic Alterations Detected by Circulating Tumor DNA in HER2-Low Metastatic Breast Cancer.

PURPOSE: About 50% of breast cancers are defined as HER2-low and may benefit from HER2-directed antibody-drug conjugates. While tissue sequencing has evaluated potential differences in genomic profiles for patients with HER2-low breast cancer, genetic alterations in circulating tumor DNA (ctDNA) have not been well described. EXPERIMENTAL DESIGN: We retrospectively analyzed 749 patients with metastatic breast cancer (MBC) and ctDNA evaluation by Guardant360 from three academic medical centers. Tumors were classified as HER2-low, HER2-0 (IHC 0) or HER2-positive. Single-nucleotide variants, copy-number variants, and oncogenic pathways were compared across the spectrum of HER2 expression. Overall survival (OS) was evaluated by HER2 status and according to oncogenic pathways. RESULTS: Patients with HER2-low had higher rates of PIK3CA mutations [relative risk ratio (RRR), 1.57; P = 0.024] compared with HER2-0 MBC. There were no differences in ERBB2 alterations or oncogenic pathways between HER2-low and HER2-0 MBC. Patients with HER2-positive MBC had more ERBB2 alterations (RRR, 12.43; P = 0.002 for amplification; RRR, 3.22; P = 0.047 for mutations, in the hormone receptor-positive cohort), fewer ERS1 mutations (RRR, 0.458; P = 0.029), and fewer ER pathway alterations (RRR, 0.321; P < 0.001). There was no difference in OS for HER2-low and HER2-0 MBC [HR, 1.01; 95% confidence interval (CI), 0.79-1.29], while OS was improved in HER2-positive MBC (HR, 0.32; 95% CI, 0.21-0.49; P < 0.001). CONCLUSIONS: We observed a higher rate of PIK3CA mutations, but no significant difference in ERBB2 alterations, oncogenic pathways, or prognosis, between patients with HER2-low and HER2-0 MBC. If validated, our findings support the conclusion that HER2-low MBC does not represent a unique biological subtype.

Society for Immunotherapy of Cancer (SITC) consensus definitions for resistance to combinations of immune checkpoint inhibitors with chemotherapy.

Although immunotherapy can offer profound clinical benefit for patients with a variety of difficult-to-treat cancers, many tumors either do not respond to upfront treatment with immune checkpoint inhibitors (ICIs) or progressive/recurrent disease occurs after an interval of initial control. Improved response rates have been demonstrated with the addition of ICIs to cytotoxic therapies, leading to approvals from the US Food and Drug Administration and regulatory agencies in other countries for ICI-chemotherapy combinations in a number of solid tumor indications, including breast, head and neck, gastric, and lung cancer. Designing trials for patients with tumors that do not respond or stop responding to treatment with immunotherapy combinations, however, is challenging without uniform definitions of resistance. Previously, the Society for Immunotherapy of Cancer (SITC) published consensus definitions for resistance to single-agent anti-programmed cell death protein 1 (PD-1). To provide guidance for clinical trial design and to support analyses of emerging molecular and cellular data surrounding mechanisms of resistance to ICI-based combinations, SITC convened a follow-up workshop in 2021 to develop consensus definitions for resistance to multiagent ICI combinations. This manuscript reports the consensus clinical definitions for combinations of ICIs and chemotherapies. Definitions for resistance to ICIs in combination with targeted therapies and with other ICIs will be published in companion volumes to this paper.

Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor-Positive (HR+)/HER2-Negative Metastatic Breast Cancer.

PURPOSE: Clinical biomarkers to identify patients unlikely to benefit from CDK4/6 inhibition (CDK4/6i) in combination with endocrine therapy (ET) are lacking. We implemented a comprehensive circulating tumor DNA (ctDNA) analysis to identify genomic features for predicting and monitoring treatment resistance. EXPERIMENTAL DESIGN: ctDNA was isolated from 216 plasma samples collected from 51 patients with hormone receptor-positive (HR+)/HER2-negative (HER2-) metastatic breast cancer (MBC) on a phase II trial of palbociclib combined with letrozole or fulvestrant (NCT03007979). Boosted whole-exome sequencing (WES) was performed at baseline and clinical progression to evaluate genomic alterations, mutational signatures, and blood tumor mutational burden (bTMB). Low-pass whole-genome sequencing was performed at baseline and serial timepoints to assess blood copy-number burden (bCNB). RESULTS: High bTMB and bCNB were associated with lack of clinical benefit and significantly shorter progression-free survival (PFS) compared with patients with low bTMB or low bCNB (all P < 0.05). Dominant APOBEC signatures were detected at baseline exclusively in cases with high bTMB (5/13, 38.5%) versus low bTMB (0/37, 0%; P = 0.0006). Alterations in ESR1 were enriched in samples with high bTMB (P = 0.0005). There was a high correlation between bTMB determined by WES and bTMB determined using a 600-gene panel (R = 0.98). During serial monitoring, an increase in bCNB score preceded radiographic progression in 12 of 18 (66.7%) patients. CONCLUSIONS: Genomic complexity detected by noninvasive profiling of bTMB and bCNB predicted poor outcomes in patients treated with ET and CDK4/6i and identified early disease progression before imaging. Novel treatment strategies including immunotherapy-based combinations should be investigated in this population.

A phase II study of palbociclib plus letrozole plus trastuzumab as neoadjuvant treatment for clinical stages II and III ER+ HER2+ breast cancer (PALTAN).

Patients with ER+/HER2+ breast cancer (BC) are less likely to achieve pathological complete response (pCR) after chemotherapy with dual HER2 blockade than ER-/HER2+ BC. Endocrine therapy plus trastuzumab is effective in advanced ER+/HER2+ BC. Inhibition of CDK4/6 and HER2 results in synergistic cell proliferation reduction. We combined palbociclib, letrozole, and trastuzumab (PLT) as a chemotherapy-sparing regimen. We evaluated neoadjuvant PLT in early ER+/HER2+ BC. Primary endpoint was pCR after 16 weeks. Research biopsies were performed for whole exome and RNA sequencing, PAM50 subtyping, and Ki67 assessment for complete cell cycle arrest (CCCA: Ki67 ≤ 2.7%). After 26 patients, accrual stopped due to futility. pCR (residual cancer burden-RCB 0) was 7.7%, RCB 0/I was 38.5%. Grade (G) 3/4 treatment-emergent adverse events occurred in 19. Among these, G3/4 neutropenia was 50%, hypertension 26.9%, and leucopenia 7.7%. Analysis indicated CCCA in 85% at C1 day 15 (C1D15), compared to 27% at surgery after palbociclib was discontinued. Baseline PAM50 subtyping identified 31.2% HER2-E, 43.8% Luminal B, and 25% Luminal A. 161 genes were differentially expressed comparing C1D15 to baseline. MKI67, TK1, CCNB1, AURKB, and PLK1 were among the genes downregulated, consistent with CCCA at C1D15. Molecular Signatures Database gene-sets analyses demonstrated downregulated processes involved in proliferation, ER and mTORC1 signaling, and DNA damage repair at C1D15, consistent with the study drug's mechanisms of action. Neoadjuvant PLT showed a pCR of 7.7% and an RCB 0/I rate of 38.5%. RNA sequencing and Ki67 data indicated potent anti-proliferative effects of study treatments. ClinicalTrials.gov- NCT02907918.

Impact of the COVID-19 pandemic on breast, colorectal, lung, and prostate cancer stage at diagnosis according to race.

PURPOSE: To determine if the COVID-19 pandemic has further exacerbated racial disparities in late-stage presentation of breast, colorectal, lung, and prostate cancers. METHODS: We conducted a registry-based retrospective study of patients with newly reported diagnoses of breast, colorectal, lung, and prostate cancers between March 2019-June 2019 (pre-COVID-19) and March 2020-June 2020 (early-COVID-19). We compared the volume of new diagnoses and stage at presentation according to race between both periods. RESULTS: During the study period, a total of 3528 patients had newly diagnosed cancer; 3304 of which had known disease stages and were included in the formal analyses. 467 (14.1%) were Blacks, and 2743 were (83%) Whites. 1216 (36.8%) had breast, 415 (12.6%) had colorectal, 827 (25%) had lung, and 846 (25.6%) had prostate cancers, respectively. The pre-COVID-19 period included 2120 (64.2%), and the early-COVID-19 period included 1184 (35.8%), representing a proportional 44.2% decline in the volume of new cases of breast, colorectal, lung, and prostate cancers, p < 0.0001. Pre-COVID-19, 16.8% were diagnosed with metastatic disease, versus 20.4% early-COVID-19, representing a proportional increase of 21.4% in the numbers of new cases with metastatic disease, p = 0.01. There was a non-significant proportional decline of 1.9% in Black patients diagnosed with non-metastatic breast, colorectal, lung, and prostate cancers early-COVID-19 (p = 0.71) and a non-significant proportional increase of 7% in Black patients diagnosed with metastatic disease (p = 0.71). Difference-in-difference analyses showed no statistically significant differences in metastatic presentation comparing Black to White patients. CONCLUSION: While we identified substantial reductions in the volume of new cancer diagnoses and increases in metastatic presentations due to the COVID-19 pandemic, the impact was similar for White and Black patients.

A randomized phase 2 study of neoadjuvant carboplatin and paclitaxel with or without atezolizumab in triple negative breast cancer (TNBC) - NCI 10013.

Atezolizumab with chemotherapy has shown improved progression-free and overall survival in patients with metastatic PD-L1 positive triple negative breast cancer (TNBC). Atezolizumab with anthracycline- and taxane-based neoadjuvant chemotherapy has also shown increased pathological complete response (pCR) rates in early TNBC. This trial evaluated neoadjuvant carboplatin and paclitaxel with or without atezolizumab in patients with clinical stages II-III TNBC. The co-primary objectives were to evaluate if chemotherapy and atezolizumab increase pCR rate and tumor infiltrating lymphocyte (TIL) percentage compared to chemotherapy alone in the mITT population. Sixty-seven patients (ages 25-78 years; median, 52 years) were randomly assigned - 22 patients to Arm A, and 45 to Arm B. Median follow up was 6.6 months. In the modified intent to treat population (all patients evaluable for the primary endpoints who received at least one dose of combination therapy), the pCR rate was 18.8% (95% CI 4.0-45.6%) in Arm A, and 55.6% (95% CI 40.0-70.4%) in Arm B (estimated treatment difference: 36.8%, 95% CI 8.5-56.6%; p = 0.018). Grade 3 or higher treatment-related adverse events occurred in 62.5% of patients in Arm A, and 57.8% of patients in Arm B. One patient in Arm B died from recurrent disease during the follow-up period. TIL percentage increased slightly from baseline to cycle 1 in both Arm A (mean ± SD: 0.6% ± 21.0%) and Arm B (5.7% ± 15.8%) (p = 0.36). Patients with pCR had higher median TIL percentages (24.8%) than those with non-pCR (14.2%) (p = 0.02). Although subgroup analyses were limited by the small sample size, PD-L1-positive patients treated with chemotherapy and atezolizumab had a pCR rate of 75% (12/16). The addition of atezolizumab to neoadjuvant carboplatin and paclitaxel resulted in a statistically significant and clinically relevant increased pCR rate in patients with clinical stages II and III TNBC. (Funded by National Cancer Institute).

Circulating tumour DNA characterisation of invasive lobular carcinoma in patients with metastatic breast cancer.

BACKGROUND: Limited data exist to characterise molecular differences in circulating tumour DNA (ctDNA) for patients with invasive lobular carcinoma (ILC). We analysed metastatic breast cancer patients with ctDNA testing to assess genomic differences among patients with ILC, invasive ductal carcinoma (IDC), and mixed histology. METHODS: We retrospectively analysed 980 clinically annotated patients (121 ILC, 792 IDC, and 67 mixed histology) from three academic centers with ctDNA evaluation by Guardant360™. Single nucleotide variations (SNVs), copy number variations (CNVs), and oncogenic pathways were compared across histologies. FINDINGS: ILC was significantly associated with HR+ HER2 negative and HER2 low. SNVs were higher in patients with ILC compared to IDC or mixed histology (Mann Whitney U test, P < 0.05). In multivariable analysis, HR+ HER2 negative ILC was significantly associated with mutations in CDH1 (odds ratio (OR) 9.4, [95% CI 3.3-27.2]), ERBB2 (OR 3.6, [95% confidence interval (CI) 1.6-8.2]), and PTEN (OR 2.5, [95% CI 1.05-5.8]) genes. CDH1 mutations were not present in the mixed histology cohort. Mutations in the PI3K pathway genes (OR 1.76 95% CI [1.18-2.64]) were more common in patients with ILC. In an independent cohort of nearly 7000 metastatic breast cancer patients, CDH1 was significantly co-mutated with targetable alterations (PIK3CA, ERBB2) and mutations associated with endocrine resistance (ARID1A, NF1, RB1, ESR1, FGFR2) (Benjamini-Hochberg Procedure, all q < 0.05). INTERPRETATION: Evaluation of ctDNA revealed differences in pathogenic alterations and oncogenic pathways across breast cancer histologies with implications for histologic classification and precision medicine treatment. FUNDING: Lynn Sage Cancer Research Foundation, OncoSET Precision Medicine Program, and UL1TR001422.

Personalized ctDNA micro-panels can monitor and predict clinical outcomes for patients with triple-negative breast cancer.

Circulating tumor DNA (ctDNA) in peripheral blood has been used to predict prognosis and therapeutic response for triple-negative breast cancer (TNBC) patients. However, previous approaches typically use large comprehensive panels of genes commonly mutated across all breast cancers. Given the reduction in sequencing costs and decreased turnaround times associated with panel generation, the objective of this study was to assess the use of custom micro-panels for tracking disease and predicting clinical outcomes for patients with TNBC. Paired tumor-normal samples from patients with TNBC were obtained at diagnosis (T0) and whole exome sequencing (WES) was performed to identify somatic variants associated with individual tumors. Custom micro-panels of 4-6 variants were created for each individual enrolled in the study. Peripheral blood was obtained at baseline, during Cycle 1 Day 3, at time of surgery, and in 3-6 month intervals after surgery to assess variant allele fraction (VAF) at different timepoints during disease course. The VAF was compared to clinical outcomes to evaluate the ability of custom micro-panels to predict pathological response, disease-free intervals, and patient relapse. A cohort of 50 individuals were evaluated for up to 48 months post-diagnosis of TNBC. In total, there were 33 patients who did not achieve pathological complete response (pCR) and seven patients developed clinical relapse. For all patients who developed clinical relapse and had peripheral blood obtained ≤ 6 months prior to relapse (n = 4), the custom ctDNA micro-panels identified molecular relapse at an average of 4.3 months prior to clinical relapse. The custom ctDNA panel results were moderately associated with pCR such that during disease monitoring, only 11% of patients with pCR had a molecular relapse, whereas 47% of patients without pCR had a molecular relapse (Chi-Square; p-value = 0.10). In this study, we show that a custom micro-panel of 4-6 markers can be effectively used to predict outcomes and monitor remission for patients with TNBC. These custom micro-panels show high sensitivity for detecting molecular relapse in advance of clinical relapse. The use of these panels could improve patient outcomes through early detection of relapse with preemptive intervention prior to symptom onset.

Proteogenomic Markers of Chemotherapy Resistance and Response in Triple-Negative Breast Cancer.

Microscaled proteogenomics was deployed to probe the molecular basis for differential response to neoadjuvant carboplatin and docetaxel combination chemotherapy for triple-negative breast cancer (TNBC). Proteomic analyses of pretreatment patient biopsies uniquely revealed metabolic pathways, including oxidative phosphorylation, adipogenesis, and fatty acid metabolism, that were associated with resistance. Both proteomics and transcriptomics revealed that sensitivity was marked by elevation of DNA repair, E2F targets, G2-M checkpoint, interferon-gamma signaling, and immune-checkpoint components. Proteogenomic analyses of somatic copy-number aberrations identified a resistance-associated 19q13.31-33 deletion where LIG1, POLD1, and XRCC1 are located. In orthogonal datasets, LIG1 (DNA ligase I) gene deletion and/or low mRNA expression levels were associated with lack of pathologic complete response, higher chromosomal instability index (CIN), and poor prognosis in TNBC, as well as carboplatin-selective resistance in TNBC preclinical models. Hemizygous loss of LIG1 was also associated with higher CIN and poor prognosis in other cancer types, demonstrating broader clinical implications. SIGNIFICANCE: Proteogenomic analysis of triple-negative breast tumors revealed a complex landscape of chemotherapy response associations, including a 19q13.31-33 somatic deletion encoding genes serving lagging-strand DNA synthesis (LIG1, POLD1, and XRCC1), that correlate with lack of pathologic response, carboplatin-selective resistance, and, in pan-cancer studies, poor prognosis and CIN. This article is highlighted in the In This Issue feature, p. 2483.

Targeted Treatment for High-Risk Early-Stage Triple-Negative Breast Cancer: Spotlight on Pembrolizumab.

Triple-negative breast cancer (TNBC) is a biologically aggressive yet heterogeneous disease that disproportionately affects younger women and women of color compared to other breast cancer subtypes. The paucity of effective targeted therapies and the prevalence of chemotherapeutic resistance in high-risk, early-stage TNBC pose significant clinical challenges. Deeper insights into the genomic and immune landscape have revealed key features of TNBC, including intrinsic genomic instability, DNA repair deficiency, and potentially an immunogenic tumor microenvironment. These advances led to landmark trials with immune checkpoint inhibitors in the advanced-stage setting, which subsequently translated into immunotherapy-based clinical trials in the early-stage setting and recent promising results. Pembrolizumab, an anti-programmed death 1 (PD-1) monoclonal antibody, was investigated in combination with platinum-, taxane- and anthracycline-based neoadjuvant chemotherapy followed by adjuvant pembrolizumab monotherapy for patients with high-risk, early-stage TNBC in the randomized, double-blind, placebo-controlled phase 3 KEYNOTE-522 trial. In July 2021, the US Food and Drug Administration (FDA) granted approval for pembrolizumab based on marked improvement in pathologic complete response rate and 3-year event-free survival compared to neoadjuvant chemotherapy alone. This advance immediately altered the longstanding treatment paradigm. Here, we review the impact of pembrolizumab plus chemotherapy for the treatment of patients with high-risk, early-stage TNBC, and discuss immunotherapy-related toxicity considerations, key immunomodulatory biomarkers under active investigation, and remaining clinical questions for future research directions.

Co-clinical FDG-PET radiomic signature in predicting response to neoadjuvant chemotherapy in triple-negative breast cancer.

PURPOSE: We sought to exploit the heterogeneity afforded by patient-derived tumor xenografts (PDX) to first, optimize and identify robust radiomic features to predict response to therapy in subtype-matched triple negative breast cancer (TNBC) PDX, and second, to implement PDX-optimized image features in a TNBC co-clinical study to predict response to therapy using machine learning (ML) algorithms. METHODS: TNBC patients and subtype-matched PDX were recruited into a co-clinical FDG-PET imaging trial to predict response to therapy. One hundred thirty-one imaging features were extracted from PDX and human-segmented tumors. Robust image features were identified based on reproducibility, cross-correlation, and volume independence. A rank importance of predictors using ReliefF was used to identify predictive radiomic features in the preclinical PDX trial in conjunction with ML algorithms: classification and regression tree (CART), Naïve Bayes (NB), and support vector machines (SVM). The top four PDX-optimized image features, defined as radiomic signatures (RadSig), from each task were then used to predict or assess response to therapy. Performance of RadSig in predicting/assessing response was compared to SUVmean, SUVmax, and lean body mass-normalized SULpeak measures. RESULTS: Sixty-four out of 131 preclinical imaging features were identified as robust. NB-RadSig performed highest in predicting and assessing response to therapy in the preclinical PDX trial. In the clinical study, the performance of SVM-RadSig and NB-RadSig to predict and assess response was practically identical and superior to SUVmean, SUVmax, and SULpeak measures. CONCLUSIONS: We optimized robust FDG-PET radiomic signatures (RadSig) to predict and assess response to therapy in the context of a co-clinical imaging trial.

Disparities in Genetic Testing for Heritable Solid-Tumor Malignancies.

Genetic testing offers providers a potentially life saving tool for identifying and intervening in high-risk individuals. However, disparities in receipt of genetic testing have been consistently demonstrated and undoubtedly have significant implications for the populations not receiving the standard of care. If correctly used, there is the potential for genetic testing to play a role in decreasing health disparities among individuals of different races and ethnicities. However, if genetic testing continues to revolutionize cancer care while being disproportionately distributed, it also has the potential to widen the existing mortality gap between various racial and ethnic populations.

Genetic Counseling and Testing in African American Patients With Breast Cancer: A Nationwide Survey of US Breast Oncologists.

PURPOSE: To determine if physicians' self-reported knowledge, attitudes, and practices regarding genetic counseling and testing (GCT) vary by patients' race. METHODS: We conducted a nationwide 49-item survey among breast oncology physicians in the United States. We queried respondents about their own demographics, clinical characteristics, knowledge, attitudes, practices, and perceived barriers in providing GCT to patients with breast cancer. RESULTS: Our survey included responses from 277 physicians (females, 58.8%; medical oncologists, 75.1%; academic physicians, 61.7%; and Whites, 67.1%). Only 1.8% indicated that they were more likely to refer a White patient than refer an African American patient for GCT, and 66.9% believed that African American women with breast cancer have lower rates of GCT than White women. Regarding perceived barriers to GCT, 63.4% of respondents indicated that African American women face more barriers than White women do and 21% felt that African American women require more information and guidance during the GCT decision-making process than White women. Although 32% of respondents indicated that lack of trust was a barrier to GCT in all patients, 58.1% felt that this was a greater barrier for African American women (P < .0001). Only 13.9% believed that noncompliance with GCT is a barrier for all patients, whereas 30.6% believed that African American women are more likely than White women to be noncompliant (P < .0001). CONCLUSION: We demonstrated that racial differences exist in oncology physicians' perceived barriers to GCT for patients with breast cancer. This nationwide survey will serve as a basis for understanding physicians' determinants of GCT for African American women and highlights the necessity of education and interventions to address bias among physicians. Awareness of such physician biases can enable further work to address inequities, ultimately leading to improved GCT equity for African American women with breast cancer.

Immunogenomic profiling and pathological response results from a clinical trial of docetaxel and carboplatin in triple-negative breast cancer.

PURPOSE: Patients with triple-negative breast cancer (TNBC) who do not achieve pathological complete response (pCR) following neoadjuvant chemotherapy have a high risk of recurrence and death. Molecular characterization may identify patients unlikely to achieve pCR. This neoadjuvant trial was conducted to determine the pCR rate with docetaxel and carboplatin and to identify molecular alterations and/or immune gene signatures predicting pCR. EXPERIMENTAL DESIGN: Patients with clinical stages II/III TNBC received 6 cycles of docetaxel and carboplatin. The primary objective was to determine if neoadjuvant docetaxel and carboplatin would increase the pCR rate in TNBC compared to historical expectations. We performed whole-exome sequencing (WES) and immune profiling on pre-treatment tumor samples to identify alterations that may predict pCR. Thirteen matching on-treatment samples were also analyzed to assess changes in molecular profiles. RESULTS: Fifty-eight of 127 (45.7%) patients achieved pCR. There was a non-significant trend toward higher mutation burden for patients with residual cancer burden (RCB) 0/I versus RCB II/III (median 80 versus 68 variants, p 0.88). TP53 was the most frequently mutated gene, observed in 85.7% of tumors. EGFR, RB1, RAD51AP2, SDK2, L1CAM, KPRP, PCDHA1, CACNA1S, CFAP58, COL22A1, and COL4A5 mutations were observed almost exclusively in pre-treatment samples from patients who achieved pCR. Seven mutations in PCDHA1 were observed in pre-treatment samples from patients who did not achieve pCR. Several immune gene signatures including IDO1, PD-L1, interferon gamma signaling, CTLA4, cytotoxicity, tumor inflammation signature, inflammatory chemokines, cytotoxic cells, lymphoid, PD-L2, exhausted CD8, Tregs, and immunoproteasome were upregulated in pre-treatment samples from patients who achieved pCR. CONCLUSION: Neoadjuvant docetaxel and carboplatin resulted in a pCR of 45.7%. WES and immune profiling differentiated patients with and without pCR. TRIAL REGISTRATION: Clinical trial information: NCT02124902, Registered 24 April 2014 & NCT02547987, Registered 10 September 2015.

Early Assessment Window for Predicting Breast Cancer Neoadjuvant Therapy using Biomarkers, Ultrasound, and Diffuse Optical Tomography.

PURPOSE: The purpose of the study was to assess the utility of tumor biomarkers, ultrasound (US) and US-guided diffuse optical tomography (DOT) in early prediction of breast cancer response to neoadjuvant therapy (NAT). METHODS: This prospective HIPAA compliant study was approved by the institutional review board. Forty one patients were imaged with US and US-guided DOT prior to NAT, at completion of the first three treatment cycles, and prior to definitive surgery from February 2017 to January 2020. Miller-Payne grading was used to assess pathologic response. Receiver operating characteristic curves (ROCs) were derived from logistic regression using independent variables, including: tumor biomarkers, US maximum diameter, percentage reduction of the diameter (%US), pretreatment maximum total hemoglobin concentration (HbT) and percentage reduction in HbT (%HbT) at different treatment time points. Resulting ROCs were compared using area under the curve (AUC). Statistical significance was tested using two-sided two-sample student t-test with P < 0.05 considered statistically significant. Logistic regression was used for ROC analysis. RESULTS: Thirty-eight patients (mean age = 47, range 24-71 years) successfully completed the study, including 15 HER2 + of which 11 were ER + ; 12 ER + or PR + /HER2-, and 11 triple negative. The combination of HER2 and ER biomarkers, %HbT at the end of cycle 1 (EOC1) and %US (EOC1) provided the best early prediction, AUC = 0.941 (95% CI 0.869-1.0). Similarly an AUC of 0.910 (95% CI 0.810-1.0) with %US (EOC1) and %HbT (EOC1) can be achieved independent of HER2 and ER status. The most accurate prediction, AUC = 0.974 (95% CI 0.933-1.0), was achieved with %US at EOC1 and %HbT (EOC3) independent of biomarker status. CONCLUSION: The combined use of tumor HER2 and ER status, US, and US-guided DOT may provide accurate prediction of NAT response as early as the completion of the first treatment cycle. CLINICAL TRIAL REGISTRATION NUMBER: NCT02891681. https://clinicaltrials.gov/ct2/show/NCT02891681 , Registration time: September 7, 2016.

Racial differences in no-show rates for screening mammography.

BACKGROUND: Differences in utilization of screening mammography partly explain the increased breast cancer mortality observed in African American (AA) women compared with non-Hispanic White women. However, the contribution of noncompliance from women who do not come for their scheduled screening mammography appointment (ie, no-shows) is unknown. The purpose of this study was to investigate racial differences in no-show rates for screening mammography. METHODS: Women scheduled for routine screening mammograms between January 2018 and March 2018 were identified from the Joanne Knight Breast Health Center at Siteman Cancer Center in St. Louis, Missouri. Using a case-control design, this study retrospectively identified patients who no-showed for their mammograms (cases) and randomly sampled an equal number of patients who completed their mammograms (controls). These participants were compared by race. The main outcome measure was whether AA race was associated with no-shows for screening mammography. RESULTS: During the study period, 5060 women were scheduled for screening mammography, and 316 (6.2%) did not keep their appointment (ie, they no-showed). Women who no-showed were more likely to be AA than women who kept their appointment (odds ratio, 2.64; 95% confidence interval, 1.90-3.67). Even after adjustments for marital status, insurance type, and place of residence, AA race was still significantly associated with no-shows for screening mammography. CONCLUSIONS: This study identified a no-show rate of 6.2% for screening mammography at the authors' institution. Women who no-showed were more likely to be AA than women who completed their mammogram even after adjustments for multiple factors. These data can be leveraged for future studies aimed at improving mammography attendance rates among AA women.

Optimal co-clinical radiomics: Sensitivity of radiomic features to tumour volume, image noise and resolution in co-clinical T1-weighted and T2-weighted magnetic resonance imaging.

BACKGROUND: Radiomics analyses has been proposed to interrogate the biology of tumour as well as to predict/assess response to therapy in vivo. The objective of this work was to assess the sensitivity of radiomics features to noise, resolution, and tumour volume in the context of a co-clinical trial. METHODS: Triple negative breast cancer (TNBC) patients were recruited into an ongoing co-clinical imaging trial. Sub-typed matched TNBC patient-derived tumour xenografts (PDX) were generated to investigate optimal co-clinical MR radiomic features. The MR imaging protocol included T1-weighed and T2-weighted imaging. To test the sensitivity of radiomics to resolution, PDX were imaged at three different resolutions. Multiple sets of images with varying signal-to-noise ratio (SNR) were generated, and an image independent patch-based method was implemented to measure the noise levels. Forty-eight radiomic features were extracted from manually segmented 2D and 3D segmented tumours and normal tissues of T1- and T2- weighted co-clinical MR images. FINDINGS: Sixteen radiomics features were identified as volume dependent and corrected for volume-dependency following normalization. Features from grey-level run-length matrix (GLRLM), grey-level size zone matrix (GLSZM) were identified as most sensitive to noise. Radiomic features Kurtosis and Run-length variance (RLV) from GLSZM were most sensitive to changes in resolution in both T1w and T2w MRI. In general, 3D radiomic features were more robust compared to 2D (single slice) measures, although the former exhibited higher variability between subjects. INTERPRETATION: Tumour volume, noise characteristics, and image resolution significantly impact radiomic analysis in co-clinical studies.