bluuebunny/crossref_metadata_2025_split huggingface dataset:
Outcomes of Lynch syndrome (LS) patients treated with immune checkpoint inhibitors (ICI).
Authors: Bari Shahla , Kim Richard D. , Wang Xia , Matejcic Marco , Muzaffar Jameel 
Published: May 2020

1548 Background: LS is caused by a germline mutation in one of several DNA mismatch repair (MMR) genes: MLH1, MSH2, MSH6 or PMS2 (d-MMR). A minority of LS patients have MMR proficient tumors (p-MMR). ICI therapy has dramatically changed outcome of d-MMR (majority of LS patients. However, data about response to ICI in LS patients, irrespective of their tumor MMR status is scarce. The aim of this study was to evaluate outcomes of ICI therapy in all LS associated Cancer. Methods: This was a retrospective analysis of LS associated cancers treated with one of the 6 ICIs at our center. We also looked at age, sex, microsatellite status, response and survival. Results: Out of 262 LS patients analyzed, 194 had cancer and 22 received ICIs. Among the patients analyzed, the mean age at diagnosis of 1st cancer was 51 yrs. There were 10 females (47%). 10 patients had colorectal (45%), 3 urothelial (14%), 2 renal cell, 2 cholangiocarcinoma and one each of esophageal, ovarian, uterine, glioblastoma multiforme and pancreatic cancer. One patient died from progressive disease after receiving a single dose and was not included in the analysis. 17 patients (80%) received Pembrolizumab, 11 patients were microsatellite unstable (MSI), 3 were microsatellite stable (MSS) while 7 were unknown. 2 patients achieved complete response (CR) (10%), 1 patient had partial response (PR) (5%), 13 had stable disease (62%) while 5 had progressive disease (23%) leading to a disease control rate (DCR) of 76%. Of the 3 known MSS Lynch syndrome patients, 2 did not respond while the 3rd continues to respond at 9 months of therapy. Of the 5 patients who had PD, 2 were MSS, 2 unknown and 1 MSI. Among the 16 patients who responded, 15 of 16 (94%) had sustained response and have not experienced disease progression or relapse. 3 of these patients have been off therapy (1 due to immune related adverse evet) and have had no relapse. One responder progressed after 18 cycles of therapy. The DCR was 71% at 12 months as well as 48 months of follow up. Median progression survival has not been reached. Similarly, median overall survival has not been reached. Conclusions: Our study is the one of the largest reported analysis of LS associated cancer patients treated with ICIs and included LS patients with both MSI and MSS tumors. Though small, our data suggests robust DCR and prolonged responses in Lynch associated MSS tumors treated with ICI. This encouraging response in MSS tumors along with higher response rates in LS associated cancers as compared to non-LS MSI tumors, suggests that there may be additional drivers of response to ICI in LS patients leading to superior responses.
Clinicopathologic features of invasive breast cancer (BC) diagnosed in carriers of germline PALB2, CHEK2 and ATM pathogenic variants.
Authors: Scott Danika , Kingham Kerry , Hodan Rachel , Ma Cindy , Mills Meredith , Ford James M. , Kurian Allison W. , Telli Melinda L. 
Published: May 2020

1549 Background: While germline pathogenic variants (PVs) in BRCA1/2 account for a large proportion of hereditary breast cancer (BC), PVs in PALB2, CHEK2 and ATM are increasingly detected. However, the phenotype and clinical features of invasive BC with these PVs have not been fully described. Methods: We identified patients with a PV or likely PV in PALB2, CHEK2 or ATM tested clinically at Stanford between 2014 - 2019 who provided informed consent to be included in a prospective cancer genetics registry. Data on baseline demographics, genetic testing history, and clinicopathologic features of diagnosed BC were collected. For patients with a subsequent diagnosis of metastatic BC, we calculated disease-free interval (DFI). Results: 130 patients met inclusion criteria for analysis: ATM (N=39), CHEK2 (N=58), PALB2 (N=33). Nearly all (98.5%) were women, with 2 male BC in ATM carriers. Non-Hispanic White ethnicity was most common in ATM (64.1%, 95% CI 48.4%-77.3%) and CHEK2 carriers (69.0%, 95% CI 56.1%-79.4%), but comprised only 39.4% (95% CI 24.7%-56.4%) in PALB2 carriers. Asian/Pacific Islander (24.2%, 95% CI 12.6%-41.3%) and Hispanic (30.3%, 95% CI 17.3%-47.5%) ethnicities were enriched among PALB2 mutation carriers. In total, 97.7% learned of their PV status only after a preceding diagnosis of BC and 43.1% were diagnosed with BC at age ≤ 45. Data regarding invasive BC subtypes, incidence of subsequent primary BC, and metastatic recurrence are listed below in the table. Additional data on stage, grade and sites of metastatic spread will be presented. Conclusions: We observed clinically important differences in the spectrum of BC subtypes among carriers of ATM, CHEK2 and PALB2 PVs, in addition to racial/ethnic differences with Asian/Pacific Islander and Hispanic ethnicity enriched among carriers of PALB2 PVs. [Table: see text]
A noninvasive multi-analytic approach for lung cancer screening of patients with pulmonary nodules.
Authors: Zheng Hong , Han Tiancheng , Liu Quanxing , Zhou Dong , Jiang Li , Hou Bin , Lu Xiao , Li Qingyuan , Zhihua Pei , Hong Yuanyuan , Zhang Yaxi , Chen Weizhi , He Ji , Dai Jigang 
Published: May 2020

1550 Background: Low-dose computed tomography (LDCT) is an effective approach for lung cancer screening of high-risk patients with pulmonary nodules, however with varying false positive rates depending on the somewhat subjective judgement of the practice professional. Artificial intelligence derived from machine learning of comprehensive patient profiles, including multi-omics and clinical data, has the potential to provide more objective assessment of patient’s risk in order to aid clinician’s decision making. We have developed a multi-analyte algorithm-based assay (MAAA) that incorporates ctDNA mutation, ctDNA methylation, and protein biomarker profiles evaluated through non-invasive blood-based testing, as well as patient’s clinical information, to improve the diagnostic efficacy of lung cancer. Methods: 98 high-risk patients with pulmonary nodules were enrolled in two independent cohorts (68 for training/testing and 30 for independent validation). The malignancy of the pulmonary nodules were established through pathology of surgical-removed nodules. Prior to surgery, each patient was also subject to cell-free DNA-based sequencing for DNA mutation and DNA methylation profiling, as well as serum protein biomarker profiling. On the training/testing patient cohort, machine-learning-based predictive models were first built for malignancy status prediction based on each type of molecular or clinical features. A final ensemble model was then constructed to incorporate the measurements based on molecular and clinical markers to provide the ultimate recommendation on the malignancy of the pulmonary nodule. The performance of each individual model and the final ensemble model was benchmarked on the training/testing cohort, and also validated on the independent validation cohort. Results: On the 30-patient independent validation cohort, individual prediction models based on clinical information, protein marker, ctDNA mutation, and ctDNA methylation profiles achieved predictive AUC of 0.59, 0.48, 0.71, and 0.84, respectively. The final ensemble model achieved predictive AUC of 0.86, which has strongly indicated that an integrative, algorithm-based approach of multi-analytic molecular and clinical profiles greatly outperforms any single-analytic profiling. Conclusions: Multi-analyte algorithm-based approach can be utilized to assist in lung cancer screening for patients with pulmonary nodules. It has demostrated a high accuracy through independent validation, and has outperformed any single-analyte testing in our study.
Green tea extract to prevent colorectal adenomas in men and women: Results of the MIRACLE trial.
Authors: Ettrich Thomas Jens , Stingl Julia , Menzler Stefan , Messmann Helmut , Kleber Gerhard , Zipprich Alexander , Frank-Gleich Stefanie , Algül Hana , Metter Klaus , Odemar Frank , Heuer Theodor , Hügle Ullrich , Behrens Rüdiger , Berger Andreas , Scholl Catharina , Schneider Katharina , Perkhofer Lukas , Rohlmann Friederike , Muche Rainer , Seufferlein Thomas 
Published: May 2020

1551 Background: Prevention of colorectal adenomas (CA) can reduce colorectal cancers (CRC). Epidemiological and experimental data suggest that the green tea catechin epigallocatechingallate has an antineoplastic effect in the large bowel. MIRACLE is the largest trial so far to examine the effect of three-year daily intake of green tea extract (GTE) on the incidence of metachronous CA in a Caucasian population. Methods: Prospective, parallel group, double-blinded, placebo-controlled, randomized multicenter trial (40 German centers, recruitment 11/2011-6/2015). Patients (n = 1001, age 50-80y), polypectomy ≤ 6 months and tolerating GTE well (one-month run-in) were randomized to receive decaffeinated GTE standardized to EGCG (150 mg bid, capsules) or placebo (P) for 3 years. Primary endpoint: Incidence of metachronous CA at the 3-year follow-up colonoscopy. Secondary endpoints: Occurrence, number, localization, size, histological subtype of CA, frequency of CRC, biomarker and safety. Strata: study center, low-dose aspirin (≤100 mg/d). Results: Clinical parameters were well balanced. CA incidence at the 3-year follow-up colonoscopy was analyzed in the modified ITT set (modITT; n = 309 patients (GTE), n = 323 (placebo), timely follow up colonoscopy) and the per protocol set (PP, modITT set without major protocol violations). Incidence of CA was 55.7 % (P) and 51.1% (GTE), (modITT, adj. RR 0.905, one sided, p = 0.081), respectively 54.3 % (P) and 48.3% (GTE) (PP, adj. RR 0.883, one sided, p = 0.058). These differences did not reach statistical significance. In the preplanned exploratory analysis regarding gender incidence of CA in females was 47.9% (P) and 47.6% (GTE) in the modITT-set (adj. RR 0.989; 95%-CI: 0.753,1.299; p = 0.935), respectively 45.4% (P) and 46.9% (GTE) in the PP-set (adj. RR 1.014; 95%-CI: 0.748, 1.373; p = 0.930). In contrast, in the male population incidence of CA in the follow-up colonoscopy was 60.4% (P) and 52.9% (GTE) in the modITT-set (adj. RR 0.846; 95% CI 0.717, 0.999); p = 0.048), respectively 59.1% (P) and 49.1% (GTE) in the PP-set (RR 0.803, 95% CI: 0.666, 0.969; p = 0.022). Thus, GTE intake was associated with a significant, 12.4 relative and 7.5% absolute reduction of metachronous CA in the male modITT population. There were no differences with respect to safety between the groups. Conclusions: GTE reduced the incidence of metachronous CA. However, a significant effect was only observed in the in the male population whereas there was no effect in the female population. Clinical trial information: NCT 01360320.
3,3'-Diindolylmethane (DIM): A nutritional intervention and its impact on breast density in healthy BRCA carriers compared to non-treated carriers—A prospective clinical trial.
Authors: Yerushalmi Rinat , Bargil Sharon , Ber Yaara , Ozalvo Rachel , Sela Sivan , Rapson Yael , Pomerantz Adi , Tsoref Dalia , Sharon Eran , Caspi Opher , Grubstein Ahuva , Margel David 
Published: May 2020

1556 Background: Women who carry the BRCA mutation are at high lifetime risk of breast cancer, but there is no consensus regarding an effective and safe chemoprevention strategy. A large body of evidence suggests that 3,3-diindolylmethane (DIM), a dimer of indole-3-carbinol (I3C) found in cruciferous vegetables, can potentially prevent carcinogenesis and tumor development. The primary aim of this prospective study was to investigate the effect of DIM supplementation on breast density, a recognized predictive factor of breast-cancer risk. Methods: Participants were 23 healthy female BRCA carriers (median age 47 years; 78% postmenopausal) who were treated with oral DIM 100 mgx1/d for one year. The amount of fibroglandular tissue (FGT) and background parenchymal enhancement (BPE) on magnetic resonance imaging (MRI) performed before and after the intervention were scored by two independent expert radiologists using the Breast Imaging and Reporting Data System (BI-RADS). Each woman in the cohort was matched by age (within 3 years) and menopausal status to a woman attending the clinic who was not participating in the study and who underwent breast MRI in parallel year. Results: A decrease in the average score for FGT amount from 2.8±0.8 at onset to 2.65±0.842.8 after one year (p = 0.031), with no significant change in BPE (p = 0.429). A group of DIM-untreated age- and menopausal-status-matched clinic patients did not show a significant change in FGT amount (p = 0.33) or BPE (p = 0.814) in a parallel year. Mean estradiol level decreased from 159 to 102 pmol/L (p = 0.01), and mean testosterone level, from 0.42 to 0.31 pmol/L (p = 0.007). Side effects were grade 1. Conclusions: One year’s supplementation with DIM 100 mgX1/d in BRCA carriers was associated with a significant decline in FGT amount on MRI. Larger randomized studies are warranted to corroborate these findings. Clinical trial information: NCT02197000.
Development of a novel liquid biopsy test to diagnose and locate gastrointestinal cancers.
Authors: Wang Yuying , Zheng Jianchao , Li Zhilong , Jiang Ruijingfang , Peng Jiaxi , Sun Jianlong , Yang Guanghui , Yang Xin-Rong , Huang Ao , Wang Yupeng , Jie Yuan , Liu Xuanhui , Gao Feng , Wu Xiaojian , WANG Dansong , Wu Wenchuan , Lou Wenhui , Zhou Jian , Fan Jia 
Published: May 2020

1557 Background: Cancers of the gastrointestinal (GI) system, including esophagus, stomach, pancreas, gallbladder, liver, bile duct, colon, and rectum are estimated to account for 38% of all cancer incidences and nearly 46% of cancer-related deaths in China. We conducted a multi-center study to evaluate the feasibility of using genetic and epigenetic abnormalities in plasma cfDNA to diagnose and locate GI cancers. Methods: We performed parallel genetic and epigenetic profiling of plasma cfDNA from hepatocellular carcinoma (HCC), colorectal cancer (CRC) and pancreatic cancer (PC) patients as well as age-matched healthy individuals by ultra-deep sequencing targeting cancer driver genes, and by targeted bisulfite sequencing covering genome-wide CpG islands, shelves, and shores. Results: Using a pre-specified mutation scoring system, we found that cfDNA mutation profiling achieved a sensitivity of 59.6%, 67.2%, and 46.8% for detecting HCC (n = 322), CRC (n = 244) and PC (n = 141) respectively, with a specificity of 95% in healthy controls (n = 207). For 901 plasma cfDNA samples that underwent methylome profiling, we first applied a machine learning approach to classify each cancer type versus healthy controls in the training cohort (HCC: n = 125; CRC: n = 105; PC: n = 97; healthy individuals: n = 84). Random Forest models with 10-fold cross validation achieved an AUC of 0.96±0.04,0.89±0.06, 0.91±0.07 for HCC, CRC, and PC, respectively. Further analyses were performed on the validation cohort, including 172 HCC patients, 162 CRC patients, 60 PC patients, and an independent cohort of healthy individuals (HCC validation: n = 63; HCC independent validation: n = 109; CRC validation: n = 104; CRC external validation: n = 58; PC validation: n = 60; healthy controls: n = 96). The trained model achieved a sensitivity of 83.1% (specificity = 95.8%), 89.5% (specificity = 95.8%), and 76.7% (specificity = 91.7%) for HCC, CRC, and PC, respectively. Using regional methylation markers from diagnostic models for individual cancer types, we built a tissue-of-origin classification model, which achieved a cross-validation accuracy of 83.3% in the training cohort and an accuracy of 80.1% in the validation cohort in assigning correct cancer types. Conclusions: Plasma cfDNA methylome profiling identified effective biomarkers for the detection and tissue-of-origin determination of GI cancers, and outperformed mutation-based detection approach. Therefore, a liquid biopsy test capable of detecting and locating GI cancers is feasible and may serve as a valuable tool for early detection and intervention.
Evaluation of circulating miRNAs for earlier cancer detection through machine-learning expression profiling.
Authors: Hsieh Jason Chia-Hsun , Liao Chun-Ta , Wang Hung-Ming , Lien Ming-Yu , Lin Yung-Chang , Shen Shih-Che , Kang Shih-Ting , Chen Wei-Ming , Hsieh Yi-Shan , Fan Ya-Chun , Yang Eric Pok Eric 
Published: May 2020

1559 Background: Earlier cancer diagnosis leads to higher patient survival rate and reduces financial burdens for patients and their families. Over the past five years, liquid biopsy has demonstrated tremendous promise in the early detection of tumor presence. In addition to circulating tumor cells and circulating tumor DNAs, extracellular microRNAs (miRNAs) have also been shown to be promising diagnostic biomarkers. Through machine-learning profiling, we sought to determine whether or not we could use individuals’ miRNA expression to distinguish between healthy subjects and cancer patients. Methods: Blood samples were collected from healthy donors and from patients of various cancer types. Plasma samples were purified within two hours of sample collection, followed by miRNA extraction. After performing reverse transcription of miRNAs into cDNAs, expression analysis of miRNAs was done using a novel multi-gene, amplification-based detection system that simultaneously analyzes over 160 miRNAs. For subsequent data processing, miRNAs without amplification signals across all profiles were first removed, resulting in 135 miRNAs. These 135 resulting miRNAs were then used as features in Support Vector Machine (SVM) to build OncoSweep classifier, a proprietary prediction algorithm for classification of the samples. Ten-fold cross validation was used to evaluate the performance of OncoSweep. Results: 344 healthy donor samples and 417 cancer patient samples were collected for the study. The prediction algorithm, OncoSweep, was derived based on the miRNA expression patterns of the healthy and the patient samples. The algorithm scored an overall accuracy for cancer prediction of 86.47%, with a sensitivity of 91.4%, a specificity of 85%, a PPV of 85% and an NPV of 88.5%. Conclusions: Utilizing machine-learning method of analyzing circulating miRNA expression profiles, the derived algorithm OncoSweep shows significant promise in cancer prediction. Validation is currently being performed in a larger study. We believe circulating miRNAs, through stringent sample processing and machine-learning methodology, are powerful biomarkers for earlier cancer detection.
Development and validation of the PREMMplus clinical prediction model for multigene hereditary cancer risk assessment.
Authors: Yurgelun Matthew B. , Uno Hajime , Furniss C. Sloane , Ukaegbu Chinedu I. , Horiguchi Miki , Chittenden Anu B. , Fehlmann Tara , Yussuf Amal , LaDuca Holly , Garber Judy Ellen , Syngal Sapna 
Published: May 2020

1579 Background: Current clinical prediction models provide syndrome-specific numeric estimates of an individual's likelihood of having a specific hereditary cancer syndrome (e.g., PREMM5 for Lynch syndrome; BRCAPRO for BRCA1/2). With the emergence of multigene panel testing (MGPT), there is a need to evaluate individuals' risk of carrying a pathogenic variant in a diverse array of cancer susceptibility genes in parallel. This study’s aim was to develop and validate the PREMMplus clinical prediction model for multigene cancer risk assessment. Methods: PREMMplus was developed in a cohort of 7296 individuals who had undergone germline MGPT at a single center. Logistic regression models were used to examine candidate predictive variables – including age, sex, ethnicity, and personal/family history of cancer – to provide a numeric estimate of an individual’s likelihood of carrying a pathogenic/likely pathogenic germline variant in one of 18 cancer susceptibility genes (11 high- [ APC, BRCA1/2, CDH1, EPCAM, MLH1, MSH2, MSH6, biallelic MUTYH, PMS2, and TP53] and 7 moderate-penetrance [ ATM, CDKN2A, CHEK2, PALB2, PTEN, RAD51C, and RAD51D]). Model performance was validated in an independent dataset of 14845 individuals who had undergone MGPT at a commercial laboratory. Results: Using clinical characteristics, including personal/family history of 18 cancers plus colorectal adenoma burden, PREMMplus demonstrated an excellent ability to predict pathogenic variants in high penetrance genes at 90% sensitivity. PREMMplus had acceptable performance with the addition of 7 moderate penetrance genes. PREMMplus was well-calibrated and demonstrated comparable performance in the external validation dataset. Conclusions: PREMMplus is the first validated risk assessment model to quantify an individual’s likelihood of carrying pathogenic variants in a wide diversity of cancer risk genes, and can be used to select individuals who should undergo MGPT. As expected, PREMMplus’s discriminatory capacity was reduced with the inclusion of moderate penetrance cancer risk genes. [Table: see text]
Using sequential next-generation sequencing assays to identify germline cancer predisposition variants.
Authors: Kraft Ira Lignugaris , Trottier Amy M. , Steinhardt George F. , Niu Nifang , Wanjari Pankhuri , Chen Wenjun , Segal Jeremy , Godley Lucy A. 
Published: May 2020

1581 Background: Next-generation sequencing (NGS) increasingly guides clinical care in hematological malignancies by identifying DNA mutations that change dynamically over time. Clinical samples contain variable numbers of malignant and non-malignant cells. So, careful interpretation is required to determine if a particular variant is somatic, germline, or clonal hematopoietic in origin. Methods: The University of Chicago uses a targeted NGS assay of ~1200 genes, reporting 150 as a clinical test. We aimed to identify individuals with hereditary predisposition by detecting persistent variants on sequential assays regardless of disease state. Results: 943 NGS assays from July 2017 – Feb. 2020 on 711 patients [ages 1 mo – 95 yrs, median 65 yrs] were included. 2,320 variants in 33 genes were identified with 144 patients having the same variant identified on more than one assay. Single nucleotide variants (SNVs) with variant allele frequency (VAF) ≥ 0.3 were prioritized. The first candidate gene identified with potential germline SNVs was CSF3R. 28 unique SNVs in CSF3R were found, 14 were confirmed as germline, 6 somatic, and 8 were unconfirmed due to lack of available tissue. At least 2 confirmed germline CSF3R variants were likely deleterious based on functional testing. Sequential SNVs were quantified using the coefficient of variation, characterizing each by change in VAF over time. Using a worst-case-scenario analysis, in which unconfirmed variants were not counted as germline, a computer algorithm was designed to identify potential germline variants (specificity 0.89, PPV 0.75). Via an iterative method, the algorithm compares new assays to a pool of previously reported tests, flagging patients with potential germline mutations so that biopsies may be studied in the lab, records reviewed, and referrals placed to genetic counselors. To date, 61 patients with 89 likely germline variants have been identified. Known hereditary hematological malignancy genes, such as ATM, ASXL1, CHEK2, DDX41, TSC1, and RUNX1, had the most variants identified. Limitations include the challenge in distinguishing variants that do not change over time, reliance on a targeted NGS panel, and normalizing VAF data prior to analysis. Conclusions: These data highlight the utility of NGS of bone marrow and peripheral blood samples to identify patients suspected of having germline DNA variants. In addition to identifying known predisposition syndromes, one may discover new inherited cancer syndromes and help guide clinical practice in real time.