tbuckley/cabot-search huggingface dataset:
Glioblastoma gene expression subtypes and correlation with clinical, molecular and immunohistochemical characteristics in a homogenously treated cohort: GLIOCAT project.
Authors: Estela Pineda, Anna Esteve-Codina, Maria Martinez-Garcia, Francesc Alameda, Cristina Carrato, Oriol Arpi, Iban Aldecoa, Silvia Menendez, Teresa Ribalta, Noemi Vidal Sarro, Sonia Del Barco Berron, Anna Estival, Oscar Gallego, Miguel J. Gil Gil, Carlos Mesia Barroso, Jordi Craven, Salvador Villa, Rafel Fuentes, Núria de la Iglesia, Carmen Balana
Journal: Journal of Clinical Oncology (2019)

2029 Background: Glioblastoma (GBM) gene expression subtypes have been described in last years, data in homogeneously treated patients is lacking. Methods: Clinical, molecular and immunohistochemistry (IHC) analysis from patients with newly diagnosed GBM homogeneously treated with standard radiochemotherapy were studied. Samples were classified based on the expression profiles into three different subtypes (classical, mesenchymal, proneural) using Support Vector Machine (SVM), the K-nearest neighbor (K-NN) and the single sample Gene Set Enrichment Analysis (ssGSEA) classification algorithms provided by GlioVis web application. Results: GLIOCAT Project recruited 432 patients from 6 catalan institutions, all of whom received standard first-line treatment (2004 -2015). Best paraffin tissue samples were selected for RNAseq and reliable data were obtained from 124. 82 cases (66%) were classified into the same subtype by all three classification algorithms. SVM and ssGEA algorithms obtain more similar results (87%). No differences in clinical variables were found between the 3 GBM subtypes. Proneural subtype was enriched with IDH1 mutated and G-CIMP positive tumors. Mesenchymal subtype (SVM) was enriched in unmethylated MGMT tumors (p = 0.008), and classical (SVM) in methylated MGMT tumors (p = 0.008). Long survivors ( &gt; 30 months) were rarely classified as mesenchymal (0-7.5%) and were more frequently classified as Proneural (23.1-26.). Clinical (age, resection, KPS) and molecular ( IDH1, MGMT) known prognostic factors were confirmed in this serie. Overall, no differences in prognosis were observed between 3 subtypes, but a trend to worse survival in mesenchymal was observed in K-NN (9.6 vs 15 ). Mesenchymal subtype presented less expression of Olig2 (p &lt; 0.001) and SOX2 (p = 0.003) by IHC, but more YLK-40 expression (p = 0.023, SVM). On the other hand, classical subtype expressed more Nestin (p = 0.004) compared to the other subtypes (K-NN). Conclusions: In our study we have not found correlation between glioblastoma expression subtype and outcome. This large serie provides reproducible data regarding clinical-molecular-immunohistochemistry features of glioblastoma genetic subtypes.
Impact of systemic treatment associated to radiotherapy on quality of life in locally advanced head and neck cancer patients in Brazil: Prospective real-world data study.
Authors: Marcos Antonio Santos, Luis Felipe Oliveira e Silva, Hugo Fontan Kohler, Otavio Curioni, Ricardo Alencar Vilela, Marcel Fang, Carmen Silvia Passos Lima, João Pedro Perez Gomes, Aline Lauda Freitas Chaves, Jose Zago Pulido, Karine Trindade, Mauricio C. Araujo, Fernando Obst, Janaina Brollo, Ediane Ferreira, Luiz Paulo Kowalski, Christian Domenge
Journal: Journal of Clinical Oncology (2019)

e17563 Background: the purpose of this study was to compare quality of life (QoL) and overall survival (OS) in patients with locally advanced head and neck cancer treated with radiotherapy only (RT), chemoradiotherapy with cisplatin (CT-RT) or RT with cetuximab (CET-RT). Methods: in this real-world, multi-institutional and prospective study, QoL outcomes were assessed using EORTC QLQ-C30 and QLQ-H&amp;N43 questionnaires. Patients were treated according to each participating institution’s protocol. The Item Response Theory was used to generate a global QoL score, based on the 71 questions of both forms. Questionnaires were completed before treatment and every three months, thereafter. Survival was calculated using the Kaplan-Meyer method, and groups were compared by the log-rank test. The impact of the treatment modalities on QoL was analyzed using multivariate regression analyses. Results: Six hundred and twenty-six patients, with tumors located at the oral cavity (36%), oropharynx (30%), larynx (21%), hypopharynx (9%) and nasopharynx (4%) were included. Median follow up was 10.2 months. RT was delivered to 39% of the patients while 58% received CT-RT and 3% received CET-RT. Patients submitted to surgery were not included. OS was higher when systemic treatment was added to RT (median OS CET-RT: 21.9 months and CT-RT: 24.3 months, versus 14.2 months with RT, p &lt; 0.05). A decrease in QoL during treatment was observed in all patients’ groups, but CT-RT had a statistically significant negative impact on QoL when compared to CET-RT (p = 0.02). An important limitation of the study is the low number of patients that received this last treatment modality, what is, probably, a result of local policies on reimbursement. Other factors that influenced QoL were alcohol consumption (better QoL for patients with no history of chronic alcohol consumption, p = 0.007) and radiotherapy technique (better QoL for patients treated with intensity-modulated RT, when compared to conformal RT, p &lt; 0.001). Conclusions: We observed, as expected, better OS with systemic therapy, when associated to RT. A decrease in QoL was detected, as well, during treatment, but a less pronounced decrease was seen in patients receiving CET-RT, when compared to CT-RT. More studies are needed to confirm the QoL improvement in patients submitted to this last treatment approach.
Selected reaction monitoring mass spectrometry (SRM-MS) evaluation of HER2 equivocal breast cancer.
Authors: William Jeffery Edenfield, Krupa Merchant, Julie C. Martin, Leylah Drusbosky, Mary Helen Elliott, Sandeep K. Reddy, Christopher Szeto, Fabiola Cecchi, Christine Schammel, David P Schammel, Rhett M Grinstead, Ki Y. Chung
Journal: Journal of Clinical Oncology (2019)

e12510 Background: Human epidermal growth factor receptor type 2 (HER2) is a significant driver of breast oncogenesis and has been found to be amplified in one-fifth of all breast cancers. Identification of cell surface over-expression of HER2 can be completed using immunohistochemistry (IHC), while amplification of the gene can be detected using fluorescence in situ hybridization (FISH) or differential polymerase chain reaction (PCR). Definitive diagnostic standards for each detection method are established, however approximately 5-10% of breast cancer patients have a HER2 status of “double equivocal,” offering little guidance to directing therapy. Previously, selected reaction monitoring mass spectrometry (SRM-MS) illustrated the dynamic range of HER2 positive protein expression by IHC or amplified FISH to have a threshold determination of 740amol.We hypothesized that this method could delineate which ‘double equivocal’ patients may indeed express enough HER2 to be candidates for targeted therapy. Methods: Overall, 76 invasive breast cancer samples identified as equivocal by IHC and FISH between 1/1/2010 and 12/31/2017 were evaluated. Typical demographic and clinicopathologic data were collected to include age, race, histology, size, hormone receptor status, treatments and outcomes. HER2 levels in each equivocal sample were quantitated using SRM-MS. Data were analyzed using Fisher’s t-tests, chi-square and ANOVA (p &lt; 0.05). Results: Using the 740 amol/ng as the SRM-MS cut-off for HER2 positivity, the group was divided into two cohorts. No significant differences were found for demographic or pathologic variables. While identified HER2 levels were between 209.1-1286.6amol, 18 patients had SRM-MS results above the threshold but outcomes were not correlated with treatment received. Conclusions: We report the largest series of doubly equivocal HER2 patients evaluated with SRM-MS. For patients with invasive ductal carcinoma, SRM-MS was not able to identify patients for whom HER2 directed therapy would be a benefit. Future plans include an assessment of this cohort with an RNA seq algorithm given the high degree of accuracy we have shown with known HER2 positives and negatives.
Rates of immunosuppressive treatment and hospitalization after checkpoint inhibitor therapy in melanoma and lung cancer patients with autoimmune diseases.
Authors: David Andrew Bender, Catherine Spina, Samuel P. Heilbroner, Eric Xanthopoulos, Tony J. C. Wang, Paul Reuscher, Brigham Hyde, Simon Cheng
Journal: Journal of Clinical Oncology (2019)

e14140 Background: Immune checkpoint inhibitors (ICIs) are known to cause immune-related adverse events. Patients with autoimmune diseases (AID) were excluded from most ICI clinical trials due to the potentially high risk of adverse effects. Data on the safety of ICIs in patients with a diagnosis of AID is therefore limited. Methods: A retrospective cohort study was conducted using a de-identified large oncology health care and pharmacy claims database with data from March 2010 until April 2017. Patients analyzed had a diagnosis of either melanoma or lung cancer and were treated with either of the anti-PD-1 inhibitors nivolumab or pembrolizumab. We assessed whether patients with AID compared with no AID were more likely to require medical interventions within 180 days of ICI therapy. We determined the percentage of patients receiving oral prednisone, IV methylprednisolone, or were hospitalized, which may represent responses to ICI toxicity. Results: 16.7% (16/96) of patients with either melanoma or lung cancer and AID received oral prednisone treatment within 180 days of ICI treatment, while 8.3% (131/1573) of patients without AID received oral prednisone during the same period. 8.4% (16/190) of patients with AID received IV methylprednisolone compared to 3.6% (79/2190) of patients without AID. Among melanoma patients, 24.1% (13/54) of patients with AID were hospitalized following ICI treatment, compared to 5.8% (28/480) of patients without ICI. Among lung cancer patients, 38.2% (52/136) of patients with AID were hospitalized compared to 31.6% (541/1711) of patients without AID. All comparisons are significant at p &lt; 0.05 except hospitalizations in lung cancer patients. Conclusions: Patients with AID were more likely to receive interventions after ICI treatment that may represent responses to immune-related adverse events, suggesting that patients with AID are at increased risk for toxicity when being treated with ICIs.
Prognosis of microsatellite instability and/or mismatch repair deficiency stage III colon cancer patients after disease recurrence: Results of an accent meta-analysis of seven studies.
Authors: Julien Taieb, Levi Pederson, Qian Shi, Steven R Alberts, Norman Wolmark, Eric Van Cutsem, Aimery De Gramont, Rachel Kerr, Axel Grothey, Sara Lonardi, Takayuki Yoshino, Greg Yothers, Thierry Andre
Journal: Journal of Clinical Oncology (2019)

3525 Background: Microsatellite instable/deficient mismatch repair (MSI) metastatic colorectal cancers have been reported to be of poor prognosis. The interaction between MSI and BRAF V600E mutation complicates the picture. Methods: Patients with resected stage III CC from 7 studies with disease recurrence and data available for MSI and BRAF V600E status were analyzed. The primary endpoint was survival after recurrence (SAR) to assess the prognostic roles of MSI and BRAF V600E , respectively. Associations of markers with SAR were analyzed using Cox proportional hazards models adjusted for clinicopathologic features (data collected 12/1998 to 11/2009). Results: Among 2630 patients with cancer recurrence (1491 men [56.7%], mean age, 58.5 [19-85] years), multivariable analysis revealed that patients with MSI tumors (n = 220) had significantly better SAR (adjusted hazard ratio [aHR], 0.82; 95% CI, 0.69-0.98; P = .029) than patients with microsatellite stable /proficient MMR (MSS) tumors (n = 1766). This was also observed when looking at patients treated by the standard FOLFOX adjuvant regimen only (aHR, 0.76; 0.58-1.00; P = .048). Same trends were observed when looking at MSI/dMMR patients outcome in BRAF V600E wild-type (aHR, 0.84; P = .10) and mutant (aHR, 0.88; P = .43) subgroups separately, without reaching statistical significance. As previously described poor SAR was observed in BRAF V600E mutants vs wild type patients (n = 244; aHR, 2.06; 95% CI, 1.73-2.46; P &lt; .0001) and this was also true in BRAF V600E mutants MSI/dMMR patients (n = 77, aHR, 2.65 ; 95% CI, 1.67-4.21; p &lt; .0001). Other factors associated with a poor SAR were : olderage, male gender, T4/N2, proximal primary tumor location, poorly differentiated adenocarcinoma, and early recurrence (by 1y increase). Conclusions: In stage III colon cancer patients recurring after adjuvant chemotherapy and before the era of immuno-oncologic agents, MSI/dMMR was associated with a better survival compared to MSS. BRAF V600E mutation seems to be a poor prognostic factor for both MSI/dMMR and MSS/pMMR patients.
The Circulating Cell-free Genome Atlas (CCGA) Study: Size selection of cell-free DNA (cfDNA) fragments.
Authors: Darya Filippova, Matthew H. Larson, M. Cyrus Maher, Robert Calef, Monica Pimentel, Yiqi Zhou, Joshua Newman, Samuel Gross, Virgil Nicula, Ting-Chun Liu, Christopher Yakym, Jennifer Berman, Alex Aravanis, Arash Jamshidi
Journal: Journal of Clinical Oncology (2019)

3103 Background: Detection of somatic copy number aberrations in individuals with cancer via cfDNA whole-genome sequencing (WGS) is challenging at low tumor fractions. Given that tumor-derived cfDNA fragments are shorter than those from healthy tissues, this exploratory analysis evaluated the potential effect of size selection on the ability to detect cancer. Methods: CCGA WGS libraries were in silico and in vitro size selected to estimate the change in tumor fraction by tumor types (breast, lung, and colorectal [CRC]) and stage (I-III vs IV). In silico analyses used clinically evaluable training set samples with WGS assay results (n = 1422: 560 non-cancer [NC], 862 cancer [C] stages I-IV); classification (cancer/non-cancer) performance was estimated using fragments within the 90-150 bp range. In vitro analyses used a subset of samples (n = 93: 28 NC, 65 C stages I-IV), including C cases sampled within a range of tumor fractions; tumor fraction was also measured at each progressive removal of maximum-length fragments (intervals of 10 bp: 150 bp down to 50 bp). Results: In silico and in vitro analyses, respectively, resulted in median 2.00±0.58-fold (at 6.91±2.64X depth) and 2.00±0.52-fold (at 23±4.45X depth) increases, in overall tumor fraction (compared to non-size-selected 36X depth). This was consistent across tumor types ( in silico: 1.78±0.73 breast, 2.00±0.58 CRC, 2.00±0.41 lung; in vitro: 2.00±0.82 breast, 2.51±0.52 CRC, 2.53±0.94 lung) and stages ( in silico: 2.00±0.74 I-III, 1.78±0.52 IV; in vitro: 2.00±0.55 I-III, 1.68±0.29 IV). Tumor fraction increased with initial fragment length titrations, but not following size selection to shorter lengths ( &lt; 140 bp). Classifier trained on in silico size-selected data had increased sensitivity at 98% specificity compared to those trained on non-size-selected data (p &lt; 1e-5). Conclusions: In silico and in vitro size selection consistently increased tumor fraction across cancer types and stages, and this increase was maximized by tuning the length range of size selection. Relative to full-depth data, classification performance improved significantly. These data suggest that size selection targeting cfDNA under 140 bp may enhance cfDNA-based cancer detection. Clinical trial information: NCT02889978.
Automated artificial intelligence quantification of fibroglandular tissue on breast MRI.
Authors: Ruquaiyah Takhtawala, Nataly Tapia Negrete, Madeleine Shaver, Turkay Kart, Yang Zhang, Vivian Youngjean Park, Min Jung Kim, Min-Ying Su, Daniel S. Chow, Peter Chang
Journal: Journal of Clinical Oncology (2019)

e12071 Background: The objective of this study is to examine if a convolutional neural network can be utilized to automate breast fibroglandular tissue segmentation, a risk factor for breast cancer, on MRIs. Methods: This institutional review board approved study assessed retrospectively acquired MRI T1 pre-contrast image data for 238 patients. Ground truth parameters were derived through manual segmentation. A hybrid 3D/2D U-Net architecture was developed for fibroglandular tissue segmentation. The network was trained with T1 pre-contrast MRI data and their corresponding ground-truth labels. The analysis was started with image pre-processing. Each MRI volume was re-sampled and normalized using z-scores. Convolution operations reduced 3D volumes into a 2D slice in the contracting arm of the U-Net architecture. Results: A 5-fold cross validation was performed and the Dice similarity coefficient was used to assess the accuracy of fibroglandular tissue segmentation. Cross-validation results showed that the automated hybrid CNN approach resulted in a Dice similarity coefficient of 0.848 and a Pearson correlation of 0.961 in comparison to the ground-truth for fibroglandular breast tissue segmentation, which demonstrates high accuracy. Conclusions: The results demonstrate significant application of deep learning in accurately automating segmentation of breast fibroglandular tissue.
Case 2-1985
Authors: Richard C. Cabot, Robert E. Scully, Eugene J. Mark, Betty U. McNeely, Vincent Agnello, Robert T. McCluskey
Journal: New England Journal of Medicine (1985)

Presentation of CaseA 57-year-old woman was admitted to the hospital because of fever of unknown origin.She was well until four months earlier, in late summer, when she began to feel unwell. A physician obtained an intravenous urographic examination, which was reported to show bilateral hydronephrosis. Cystoscopic examination disclosed no evidence of obstructive uropathy, and trimethoprim–sulfamethoxazole was prescribed. Seven weeks before admission a daily fever developed, with a rise of the temperature to the range of 37.6 to 38.7°C, accompanied by shaking chills, night sweats, fatigue, dull headaches, and "cold sores" within and about the mouth. At the same . . .
17-β estradiol promotes autophagy and induces cellular senescence in breast cancer cells.
Authors: Khuloud Bajbouj, Jasmin Shafarin, Mawieh Hamad
Journal: Journal of Clinical Oncology (2019)

e12523 Background: The fact that estrogen (17-β estradiol or E2) is a known carcinogen notwithstanding, mounting evidence suggest that E2 has the potential to exert anti-cancer effects against various forms of cancer. Using in vitro models we, and others, have previously demonstrated that E2 disrupts intracellular iron metabolism in such a way that arrests cell cycling in breast and ovarian cancer cells. However, the cellular and molecular correlates underlying this cytostatic effect of E2 in cancer cells remain elusive. Methods: In this study, metastatic (MDA-MB-231) and non-metastatic (MCF-7) breast cancer cells treated with 20 nM E2 were assessed for mitochondrial function, cell proliferation, apoptosis and senescence at different time points post treatment. Results: E2 treatment resulted in a significant mitochondrial membrane depolarization; an outcome that associated with a significant loss of mitochondrial function and the accumulation of auto-phagosomes. It also significantly upregulated the expression of the cell cycle regulating cyclin-dependent kinase inhibitor, p21 protein and enhanced the activation (de-phosphorylation) of the tumour suppressor retinoblastoma (Rb) protein. Although, as previously shown, E2 did not induced classis apoptosis; it resulted in a significant elevation in senescence-associated β- galactosidase levels. Conclusions: In summary, these findings suggest that E2 treatment mediates its anti-cancer potential by disrupting mitochondrial function and precipitating autophagy and cell senescence.
Management of pediatric plaque psoriasis using biologics
Authors: Perla Lansang, James N. Bergman, Loretta Fiorillo, Marissa Joseph, Irene Lara-Corrales, Danielle Marcoux, Catherine McCuaig, Elena Pope, Vimal H. Prajapati, Sue Z.J. Li, Ian Landells
Journal: Journal of the American Academy of Dermatology (2019)
A conundrum in cancer quality measurement: Performance on long-term survival reflects performance a long time ago.
Authors: Allison Lipitz-Snyderman, Michael A. Curry, David M. Rubin, Diane G. Li, Elaine Duck, Mark H. Radzyner, Peter Bach
Journal: Journal of Clinical Oncology (2019)

e18222 Background: Long term outcomes, such as five-year survival following cancer treatment, are widely accepted as important metrics of cancer care quality. But because they take years to accrue, they reflect the quality of care delivered in the past. The objective of this study was to delineate to what extent measures of long term outcomes related to cancer care could be reliably used to predict care quality in future periods. Methods: Taking advantage of FFS Medicare data from related studies, we assessed survival of cancer patients at one and four years by hospital for four separate index years 2006, 2011-2013. We assembled pairs of years across which we could compare risk adjusted outcomes separated by one year (2011 to 2012; 2012 to 2013), two years (2011 to 2013), and five through seven years comparing 2006 to 2011, 2012, or 2013 respectively. The outcome was risk adjusted mortality rates at the hospital level determined by dividing the observed number of deaths by an expected number, adjusting for age, and median income level of the zip code of residence. For each hospital and for every pair of analytic years we separately compared the correlation of one and four-year risk adjusted mortality using both Pearson and Spearman correlation statistics. A mixed effects model was fit to determine if size and year gap between measurements could explain possible differences in the correlation of hospital performance, while controlling for hospitals as a random effect. Results: There were 1,640 hospitals and more than 350,000 patients in each analysis year. Focusing on the correlation of the four year survival outcomes, the highest volume hospitals have significantly higher correlations compared to the other hospital categories (P &lt; 0.001). The greater the elapsed time between measurement periods the lower the correlation. But in the mixed model analysis neither time elapsed between measurement periods (p = 0.51) nor the interaction between time elapsed and hospital volume (p = 0.95) were significant. Analyses of one-year outcomes produced similar findings. Conclusions: Performance on four-year survival outcomes of cancer patients was reasonably correlated for large volume hospitals, but less so for hospitals with lower volumes.