tbuckley/cabot-search huggingface dataset:
Germline mutation profile among Hispanic women with epithelial ovarian cancer (EOC).
Authors: Yanin Chavarri Guerra, Jeffrey N. Weitzel, Kathleen Reilly Blazer, Thomas Paul Slavin, Rosa Mejia, Sharon Sand, Danielle Castillo, Josef Herzog, Cynthia Villarreal-Garza, Alejandro Mohar, Yeny Rodriguez, Analí Pamela Mora Alferez, Christopher R. Hake, Terrence Cescon, Kristie Bobolis, Deborah Kerlin, Ian K. Komenaka, Patricia Rice, Darling J Horcasitas
Journal: Journal of Clinical Oncology (2019)

1584 Background: Hospital-based studies have reported a 15% prevalence of BRCA1/ BRCA2( BRCA) mutations, with a slightly higher yield of other predisposition genes on multigene panel testing (MGPT) among women with EOC, and National Comprehensive Cancer Network guidelines recommend genetic cancer risk assessment for women with EOC. However, there is limited data about the genetic epidemiology of EOC among underrepresented populations, such as Hispanics. Consequently, we determined the germline mutation profile of Hispanics with EOC, and compared them with non-Hispanics. Methods: We included all women with a personal history of EOC from the U.S. and Latin America (LatAm; Mexico, Colombia, and Peru), enrolled in the Clinical Cancer Genomics Community Research Network registry. We assessed the prevalence of pathogenic variants (PV) in BRCA1/ BRCA2( BRCA) and other genes, contrasting the germline mutation profile between Hispanics living in LatAm, U.S. Hispanics, women of Ashkenazi Jewish (AJ) ancestry in the US, and other U.S. non-Hispanics. Results: Among 1186 women with EOC (209 from LatAm, 254 U.S. Hispanics l, 78 AJ, and 645 other non-Hispanic), 262 (22%) had a PV in BRCAgenes. Hispanics from LatAm and the U.S. had a similar frequency of BRCAmutations to AJ (30.6%, 29.9%, and 38.4%, respectively; p = 0.14); while non-Hispanics showed a significantly lower frequency of BRCAmutations (14.2%, p = 0.03). The most frequently mutated gene was BRCA1(n = 197, 74.6%), followed by BRCA2(n = 67, 25.3%). Among BRCA-negative cases (n = 924), 59% (n = 545) were evaluated by MGPT and PVs were identified in 2.9% [6 Hispanics (1.2%), 3 AJ (3.8%) and 26 Non-Hispanics (4%)]), of which 66% (n = 23) were in mismatch repair genes ( MSH2, MLH1, MSH6, PMS2), and 34% (n = 12) in other EOC-associated genes ( BRIP1, NBN, PALB2, RAD51C, and RAD51D). Clinically actionable PVs in ATM (n = 4; 0.3% ) and CHEK2 (n = 6; 0.5% ) were also observed. Conclusions: Hispanics with EOC have an elevated frequency of PV, similar to that of classic founder populations such as AJ, and significantly higher than other non-Hispanics. This is partially explained by a high prevalence of recurrent LatAm-specific PV, highlighting the importance of conducting genetic studies in underrepresented populations. There was modest incremental benefit of MGPT.
A phase III, multicenter, randomized, open label trial of [fam-] trastuzumab deruxtecan (DS-8201a) versus investigator’s choice in HER2-low breast cancer.
Authors: Shanu Modi, Shoichiro Ohtani, Caleb C. Lee, Kongming Wang, Kapil Saxena, David A. Cameron
Journal: Journal of Clinical Oncology (2019)

TPS1102 Background: Human epidermal growth factor receptor 2 (HER2)-targeted therapies have greatly improved survival in HER2+ breast cancer (BC). However, there are many more BC patients with HER2-low expression (immunohistochemistry [IHC] 1+ or 2+/ in situ hybridization-negative), for whom no HER2-targeted therapies are approved. [Fam-] trastuzumab deruxtecan (T-DXd; formerly DS-8201a) is an antibody-drug conjugate with a humanized HER2 antibody, peptide-based cleavable linker, and a topoisomerase I inhibitor payload. It has a drug-to-antibody ratio of ~8 and the membrane permeability of the cleaved payload enables a cytotoxic bystander effect. In an ongoing phase 1 trial, T-DXd demonstrated an objective response rate (ORR) of 44.2% (19/43) with a manageable safety profile in heavily pretreated, advanced HER2-low BC (Oct 2018 data cutoff; Modi et al, SABCS 2018). Methods: DESTINY-Breast04 is a randomized, phase 3, 2-arm, open-label, multicenter study comparing efficacy and safety of T-DXd vs physician’s choice in HER2-low, unresectable and/or metastatic BC. Approximately 540 subjects will be randomized 2:1 to T-DXd (5.4 mg/kg intravenous every 3 weeks) or physician’s choice (capecitabine, eribulin, gemcitabine, paclitaxel, or nab-paclitaxel). Randomization is stratified by HER2 IHC status, number of prior treatments, and prior CDK4/6 inhibitor therapy/hormone receptor (HR) status. HER2 IHC will be assessed and confirmed by central testing based on archival samples. The primary efficacy endpoint is progression-free survival (PFS) per mRECIST v1.1 determined by blinded independent central review. Secondary efficacy endpoints are investigator-assessed PFS, overall survival, confirmed ORR, and duration of response. Safety endpoints include serious adverse events (AEs), treatment-emergent AEs, and AEs of special interest (interstitial lung disease/pneumonitis, cardiotoxicity, and infusion-related reactions). Primary PFS analysis will occur when 318 events are observed in HR+ subjects; providing 90% power to detect a hazard ratio of 0.68 with 1-sided α of 0.025. Enrollment began in Dec 2018. Clinical trial information: NCT03734029.
Comparison of an automated cartridge-based system for mRNA assessment with central immunohistochemistry in the neoadjuvant GeparX trial.
Authors: Carsten Denkert, Theresa Link, Paul Jank, Marianne Just, Claus Hanusch, Frank Brasch, Marion van Mackelenbergh, Willi Küster, Frederik Marme, Thomas Karn, Volkmar Müller, Sherko Kümmel, Valentina Nekljudova, Sibylle Loibl, Jens U. Blohmer
Journal: Journal of Clinical Oncology (2019)

3075 Background: Hormone receptors, HER2 and Ki-67 are prognostic values typically determined for breast cancer (BC) outcome and prediction of therapy response. A RT-qPCR based system, the Xpert Breast Cancer STRAT4, can be used to classify BC tissues regarding their hormone receptor status, HER2 and proliferation via Ki-67. We compared mRNA expression analysis of ER, PR, HER2, and Ki-67 by this automated in-vitro diagnostic platform (GeneXpert) (GX) with central immunohistochemistry (IHC) in a large clinical trial cohort. Methods: BC patients from the prospective GBG neoadjuvant trial GeparX (NCT02682693) (still recruiting) were included in this biomarker project. We used formalin-fixed paraffin embedded (FFPE) pretherapeutical core biopsies with a tumor content &gt; 10%. One 4 µm FFPE tissue section was first processed with the Xpert FFPE Lysis Kit, the sample lysate was placed in the STRAT4 cartridge system and then tested on the GX system in which the purification, amplification and real-time detection took place within two hours automatically. Results: A total of 503 (99%) of the 509 samples had a valid measurement of all four genes. 258 samples (51.3%) of the cohort were classified in central pathology as ER positive, 196 (39%) as PR positive and 78 (15.5%) as HER2-positive, and 421 samples (83.7%) were Ki-67-high ( &gt; 20%). The simple kappa coefficient was for ER = 0.7938, PR = 0.6540, HER2 = 0.8172 and Ki-67 = 0.3655. This indicates, that the measurements for ER, PR and HER2 showed a high correlation between both methods, whereas the measurement of Ki-67 does not. The accuracy between the STRAT4 and IHC was 89.7% for ER, 83.3% for PR, 94.6% for HER2 and 86.7% for Ki-67. According to molecular subgroups, highest accuracy regarding Ki-67, was determined in TNBC (96.2%; luminal: 81.1%; HER2-positive: 76.9%). Conclusions: Our results show a high concordance between standardized central IHC and automated mRNA expression analysis for the most important BC biomarkers ER, PR and HER2. For the proliferation marker Ki-67, the concordance is slightly lower. The STRAT4 assay might offer additional option to conventional methods for BC biomarker assessment, in particular in settings where IHC is not feasible. To determine the clinical validity, additional outcome analyses are necessary. Clinical trial information: NCT02682693.
p53 expression and clinical outcomes in untreated and treated breast cancer patients after long-term follow-up.
Authors: Sherry X. Yang, Erich Huang, Dat Nguyen
Journal: Journal of Clinical Oncology (2019)

e14745 Background: p53 alteration represents one of the hallmarks of malignant transformation. However, its role on treatment outcome remains controversial and is unknown in untreated patients in breast cancer. This study aims to evaluate p53 expression in association with clinical outcomes in untreated patients relative to those undergoing homogeneous therapy. Methods: p53 protein was examined by immunohistochemistry in 956 patients with stage I, II and III breast cancer. Overall survival (OS) and relapse-free survival (RFS) between p53-positive and -negative tumors in chemotherapy, radiation or endocrine therapy alone and no treatment groups were estimated by Kaplan-Meier method. OS and RFS were further assessed by multivariable Cox model that incorporates p53, age, tumor size and grade, estrogen receptor, and HER2 in specific treatment group(s). Results: p53 expression was detected in 22.7% of breast cancer. Median follow-up time was 115.5 months, with a range of 5 to 282 months. Expression of p53 was associated with younger age at diagnosis, higher tumor grade, ER/PR negativity, and HER2 positivity ( P&lt; 0.001). Without any treatment including systemic and radiation therapy (n = 227), OS and RFS curves were overlapped from the beginning until the end of follow-up between p53-positive and -negative patients, respectively. In contrast, p53 was significantly associated with worse OS and RFS with univariate analysis and multivariate statistics of OS (HR 4.07, 95% CI 1.95-8.50; P&lt; 0.001) and risk of relapse (HR 2.23, 95% CI 1.11-4.48; P= 0.025) by endocrine therapy alone (n = 130). Moreover, apparent trends for p53 toward unfavorable OS and RFS were observed in those undergoing homogeneous radiation therapy and chemotherapy, only within 150 months of follow-up. Conclusions: p53 is not associated with clinical outcomes in the absence of conventional therapy, and independently predicts worse survival and increased risk of recurrence after endocrine therapy.
Utility of tumor genomic profiling in guiding targeted therapy and referral for clinical trials in the community practice.
Authors: Yiqing Xu, Jiang Yio, Amber Yang, Ashrei Bayewitz, Daniel Benasher, Lung Fu
Journal: Journal of Clinical Oncology (2019)

e18381 Background: Next-generation sequencing (NGS), which enables tumor genomic profiling with limited tumor specimen for the guidance of targeted therapy, has been widely used in oncology practice. It also reports mutations of which no approved therapy is available, but potential therapies approved in a different tumor type may be reasonable to try, based on molecular mechanisms or limited data, either in clinical trials or off trial treatment. The utility of this information in the community practice is unclear. Methods: We performed a retrospective analysis on the usage of NGS result on patients with lung or colorectal cancers treated between November 2011 and February 2018. Patients were identified from Foundation Medicine Company database and were linked to records at Maimonides. We evaluated if NGS was used to guide FDA-approved targeted therapy, potentially-useful targeted therapy not approved for the cancer type, or referral to a clinical trial. Results: 177 patients (lung ca = 119, colon ca = 58) were included. NGS identified 34 (28.6%) lung ca patients with driver mutations, (21 EGFR, 6 RET, 3 ALK, 2 MET amplification, 1 ROS1 and 1NTRK mutation), who were all given FDA-approved therapy. 70 (58.8%) patients had at least 1 target with an FDA-approved therapy for a different cancer; 89 (74.9%) had a mutation being studied in a clinical trial, and 48 patients were eligible for the NCI-MATCH trial. None received non-FDA-approved drugs and none was referred to clinical trials. In the colon cancer cohort, NGS identified alterations in KRAS (27), BRAF (5), ERBB2 mutation (2), ERBB2 amplification (1), MLH1 (1), MSH2 (1) and BRCA 2(1). Among them, one patient received BRAF inhibitors. 45 and 24 patients were eligible for phase I/II trials and NCI-MATCH trial respectively, and none was referred. Conclusions: NGS has a high efficiency of detecting driver mutations in lung cancer; but only reveals low frequencies of alterations otherwise not tested in colon cancer. The approach of prescribing un-approved targeted treatment based on theoretical mechanism of action was very uncommon, and the referral to clinical trials was rare in this community practice, both of which decreasing the utility value of NGS.
Prediction of biomarker status, diagnosis and outcome from histology slides using deep learning-based hypothesis free feature extraction.
Authors: Eldad Klaiman, Jacob Gildenblat, Ido Ben-Shaul, Astrid Heller, Konstanty Korski, Astrid Christina Kiermaier, Fabien Gaire
Journal: Journal of Clinical Oncology (2019)

3140 Background: Recently, histological pattern signatures obtained from diagnostic H&amp;E images have been found to predict mutation, biomarker status or outcome. We report here on a novel deep learning based framework designed to identify and extract predictive histological signatures. We have applied this framework in 3 experiments, predicting specifically the microsatellite status (MSS) of colorectal cancer (CRC), breast cancer (BC) micrometastasis in Lymph nodes (LN) and Pathologic Complete Response (pCR) in BC diagnostic biopsies. Methods: Our deep learning based algorithm was trained on histology images at 20X magnification. Algorithms were trained for binary classification for each of the three cohorts. We used 75% of the images for training and test our algorithm on the remaining 25% of the images. Cohort details are as follows: MSS for CRC: 94 patients’ H&amp;E stained tissue images from the Roche internal CRC80 dataset (MSS n =24; MSI n = 70) were used. BC LN: 270 patients’ H&amp;E stained tissue images from the CAMELYON16 dataset ( LN(+) n = 110 ; LN(-), n =160) were used. pCR for BC: 225 patients’ H&amp;E stained tissue images from the Tryphaena Study BO22280, neoadjuvant, Trastuzumab/Pertuzumab chemotherapy combination trial. (pCR=111, non-pCR n=114). Results: We report and assess algorithm performance on each of the cohorts by Area Under the Curve (AUC). Prediction of MSS in the CRC80 status yielded AUC 0.9. Prediction of LN invasion on CAMELYON16 dataset yielded AUC 0.85. Prediction of pCR on the Tryphaena cohort yielded an AUC of 0.8. Conclusions: We present a new approach to generate predictive signatures based on conventional diagnostic H&amp;E images and a novel machine learning framework. The CRC80 and CAMELYON16 cohorts served as a confidence building experiments with predictive features well known by clinicians and visually confirmed. The predictive algorithm for pCR in the Tryphaena cohort yielded both response prediction and the high predictive value FOVs. These included tissue patterns which have not until now been considered to influence on the prediction of pCR.
An optimized workflow for a fast molecular diagnosis of non-small cell lung cancer.
Authors: Bing Wei, Jun Li, Pengfei Ren, Yuxi Chang, Chengzhi Zhao, Qingxin Xia, Harry J.M. Groen, Jie Ma, Yongjun Guo
Journal: Journal of Clinical Oncology (2019)

e13139 Background: Lung cancer is the most common and lethal malignancy throughout the world, in which non-small cell lung cancer (NSCLC) is the dominant subtype. To distinguish between different cell types of NSCLC, i.e. adenocarcinoma or squamous cell carcinoma, the morphologic features of cancer cells are important, as well as specific molecular markers, i.e. TTF1, p63 and p40. Genomic studies have revealed different genetic aberrations between specific subtypes of NSCLC, and distinct response to targeted therapy. Therefore, molecular testing is essential for precision diagnosis and personalized treatment. The canonical workflow from diagnosis to next generation sequencing (NGS) tests needs about two weeks. Importantly, sometimes the residue material left after diagnostic staining may not be enough for NGS tests. This means a secondary biopsy is needed, which is not patient friendly. Methods: We optimized the canonical workflow by using BIOCO, a magnetic collector attached to microtome knife holder that can collect the abandoned tissue during slicing FFPE blocks. Therefore, the material used for NGS test was collected simultaneous during slicing for pathological diagnosis. In total 123 FFPE tumor blocks from suspicious NSCLC patients were included to evaluate: 1. how long it will take from diagnosis to make treatment decision? 2. If the material collected by BIOCO is sufficient for NGS test and whether the result can be trusted. Results: 1. The BIOCO workflow only needs 7 days for the diagnosis and making therapeutic plan. 2. The BIOCO could collect enough FFPE tissue for NGS test even with HE, IHC stanning and FISH test for all the samples; however, 14 samples failed NGS test because of insufficient material left following the canonical workflow. 3. the detection sensitivity and specificity of the BIOCO method are comparable with the canonical workflow, with a consistence of 94.9%. Conclusions: Here we propose an optimized workflow by using the BIOCO collector we invented, which shortens the canonical workflow from two weeks to one week, and it fully utilizes the limited biopsy tissue for NGS testing so that the secondary biopsies are avoided.
Glucocorticoid receptor expression in Müllerian carcinosarcomas.
Authors: Meghan Steiner, Jennifer Taylor Veneris, Ricardo Lastra, S. John Weroha, Xiaonan Hou, Matthew John Maurer, Ethan P. Heinzen, Ann L. Oberg, Gini F. Fleming, Suzanne D. Conzen
Journal: Journal of Clinical Oncology (2019)

e17038 Background: Carcinosarcomas (CS) are aggressive gynecologic malignancies defined by a biphasic tumor histology of carcinomatous and sarcomatous components. High expression of glucocorticoid receptor (GR) is associated with aggressive tumor biology in triple-negative breast, ovarian, and endometrial cancers. GR activation results in transcriptional regulation of epithelial-mesenchymal transition (EMT) genes. Therefore, we hypothesized that the sarcomatous component of Müllerian CS may be associated with relatively higher GR expression compared to the carcinomatous portion. Methods: Müllerian CSs from the University of Chicago tissue bank diagnosed from 5/19/2009  8/25/2014 were identified and pathology confirmed (RL). In addition, we evaluated GR expression in a mouse PDX CS model. Immunohistochemical expression of nuclear estrogen (ER), progesterone (PR), androgen (AR), and GR was quantified using the H-score. Scores between the sarcomatous and carcinomatous components were compared using a paired t-test. Results: Mean GR H-score was relatively higher in the sarcomatous vs carcinomatous component, overall (144.44 vs 38.89, P = 0.0014). Mean H-score also differed between sarcomatous and carcinomatous components for ER (3.06 vs 63.06, P = 0.016), PR (1.67 vs 47.22, P = 0.004), and AR (0 vs 2.78, P = 0.056). The significantly higher sarcomatous GR expression was replicated in IHC evaluation of the mouse PDX model. Conclusions: GR expression is significantly higher in the sarcomatous than the carcinomatous component of Müllerian CS, while ER, PR, and AR expression is significantly lower. Recent data suggest that an EMT gene signature is more prominently expressed in the sarcomatous versus carcinomatous component. We hypothesize that GR expression and activity may mediate EMT gene expression and represent a therapeutic target for CS. [Table: see text]
Unscheduled hospitalization in advanced cancer patients: Time to rethink about the illness.
Authors: Lorena Ostios-García, Jesus Miranda Poma, Darío Sánchez Cabrero, Laura Gutiérrez Sainz, Julia Villamayor Sánchez, Alberto Alonso-Babarro, Jaime Feliu Batlle
Journal: Journal of Clinical Oncology (2019)

e23007 Background: The aim of our study was to determine if an unscheduled hospitalization in advanced cancer patients is a good time for palliative care referrals, and if this indicator could be improved with some other prognostic score. Methods: We conducted a retrospective study, which included all patients with unscheduled hospitalization in the medical oncology service from January 2011 to December 2013. In order to improve the accuracy of the analysis we considered only first admissions of each patient. We excluded patients with scheduled and unindicated hospitalization. The main variable was survival after an unscheduled hospitalization. We collected the following variables: demographic (age, sex, date of birth, date of death and place of death), tumor type, clinical variables (reason for admission, date of hospitalization, assessment by the palliative care unit during hospitalization, date of last chemotherapy and ECOG), analytical variables (albumin, lymphocytes and lactate dehydrogenase) and a prognostic nomogram developed by our team. Results: Inclusion criteria were met by 1,180 patients. Table summarizes the main sociodemographic characteristics, the type of tumor, and the functional status of patients according to the ECOG scale. After two years of follow-up, 816 (69%) patients had died. The median overall survival was 188 days (161-214). Patients with breast and gynecological cancer had the longest survival, while patients with melanoma, gastric cancer, lung cancer, and pancreatic cancer had the poorest survival. 676 patients (58%) were readmitted during the following year. Readmissions meant a significant decrease of survival. The stage of the oncological disease and performance status measured by ECOG had a clear relationship with survival time. Prognostic nomogram showed high accuracy to predict the probability of survival. Median survival for different quartile was respectively: 348, 139, 68 and 31 days (p &lt; 0´000). Conclusions: The median survival of patients after an unscheduled hospitalization was around 6 months. Been admitted seems a good indicator to introduce specific palliative care. The use of other prognostic scores, as a prognostic nomogram, could help to select patient’ groups with poorer survivals. [Table: see text]