tbuckley/cabot-search huggingface dataset:
A novel computational tool for copy number variation detection in targeted circulating tumor DNA.
Authors: Jianing Yu, Tiancheng Han, Xiaojing Lin, Xue Song, Hongyu Xie, Ji He, Weizhi Chen
Journal: Journal of Clinical Oncology (2019)

e13051 Background: Targeted sequencing of circulating tumor DNA (ctDNA) has been used in early tumor detection and guidance of clinical cancer treatment. Accurate somatic copy number variation (SCNV) estimation is useful for better decisions in clinics, but remain challenging due to low percentage of tumor-cell-released DNA in circulating blood, in addition to the low signal-noise ratio and usual lack of normal control. Methods: To overcome these challenges and call SCNV at gene level, we develop a novel bioinformatics tool ctCNV. After correction for GC content, target region length and read counts, genome local scores at the gene level (GCS) were calculated, using 30 normal blood samples as control. Statistically significant cutoffs were determined using control. Results: The new method has been benchmarked with other SCNV calling tools such as CNVkit, which have been developed mainly for whole exome sequencing instead of targeted DNAseq. The validation experiment involves 6 mixed samples consisting of different proportions of known cell lines and real blood samples. ROC curve obtained through comparing the SCNV calling results with Droplet Digital PCR results show improvement of our method comparing to existing methods. Conclusions: As a summary, our study has three main results/contributions. First, we developed a novel computational tool for SCNV calling in targeted sequencing of ctDNA, with good sensitivity and specificity. Second, we thoroughly evaluated the performance of current available CNV calling tools in targeted sequenced ctDNA. Third, the raw data generated from our six real samples of gradient mixture of different cell lines and human’s samples can serve as an evaluation standard to other further computational tools for CNV calling in targeted sequenced ctDNA.
Phase II study of avelumab in multiple relapsed/refractory testicular germ cell cancer.
Authors: Michal Mego, Daniela Svetlovska, Michal Chovanec, Katarina Rejlekova, Jana Obertova, Patrik Palacka, Zuzana Sycova-Mila, Ugo De Giorgi, Jozef Mardiak
Journal: Journal of Clinical Oncology (2019)

e16045 Background: Testicular germ cell tumors (TGCTs) represent a highly curable disease; however, a small proportion of patients develop disease recurrence. PD-L1 expression is significantly higher in germ cell tumors (GCTs) in comparison to normal testicular tissue and high PD-L1 expression is associated with inferior progression-free and overall survival compared to patients with low PD-L1 expression. This study aimed to determine the efficacy and toxicity of PD-L1 antagonist, Avelumab, in patients with refractory GCTs. Methods: From November 2017 to January 2018, 8 patients with refractory GCTs were enrolled in the phase II study. All patients were pretreated with at least 2 cisplatin-based therapies (median 5, range 2 – 6); 5 tumors (62.5%) were absolutely refractory to cisplatin and 5 patients (62.5%) had visceral non-pulmonary metastases. Avelumab was administered at a dose of 10mg/kg biweekly until progression or unacceptable toxicity. The primary end point was 12-weeks progression-free survival (PFS). If &lt; 8 responses to study therapy will be observed among the first 15 patients, the study will be terminated. Results: Median age was 29 years (range: 22 – 52 years). During a median follow-up period of 2.6 months (range: 0.3 - 14.4), 7 (87.5%) patients experienced disease progression and 6 patients (80.0%) died. Twelve-week PFS was 0%, median PFS was 1.4 months, 95%CI (0.9 – 1.4) and median OS was 2.7 months, 95% CI (1.0 – 3.3). No objective response was observed. Avelumab was well tolerated, no severe adverse event was observed. Conclusions: This study failed to achieve its primary end point and our data suggest lack of Avelumab efficacy in unselected multiple relapsed/refractory TGCTs. Clinical trial information: NCT03403777.
Systemic Treatment Options in Hepatocellular Carcinoma
Authors: Lorenza Rimassa, Tiziana Pressiani, Philippe Merle
Journal: Liver Cancer (2019)

Patients with advanced hepatocellular carcinoma (HCC) typically have poor survival outcomes. Until recently, sorafenib was the only systemic therapy option available and no agents were approved after sorafenib failure. However, rapid changes are beginning to emerge in the treatment landscape of advanced HCC, with approvals of regorafenib, nivolu-mab, lenvatinib, pembrolizumab, and cabozantinib and positive phase II/III clinical trial results with other agents.Here, we provide a comprehensive overview of the clinical trial data of systemic agents that are currently approved for advanced HCC (sorafenib, regorafenib, and nivolumab), including agents recently approved in 2018 (lenvatinib, pembrolizumab, and cabozantinib) and those with recent positive phase II/III results (ramucirumab). Key features of the clinical trial design, including patient selection criteria, the use of biomarkers in HCC, and criteria for efficacy assessment, and their implications in real-world practice are discussed. Important ongoing and planned trials in advanced HCC are summarized to provide a glimpse into the future of advanced HCC treatment. From a physician's viewpoint, the treatment algorithms for advanced HCC are undergoing significant changes, as additional and imminent approvals impact the choices of first- and second-line treatment and decisions regarding the timing of therapy initiation. With these additional choices at hand, treatment sequencing remains a complex task and should take patient selection and tolerance profiles into account.The treatment of advanced HCC remains challenging and complex. The rapid developments in systemic therapy for advanced HCC should be considered when determining the best choice and sequence of treatment for patients with advanced HCC.
Case 48-1980
Authors: Richard C. Cabot, Robert E. Scully, James J. Galdabini, Betty U. McNeely, Walter G. Bradley, Bhagwan T. Shahani, Newton E. Hyslop
Journal: New England Journal of Medicine (1980)

Presentation of CaseA 47-year-old man was admitted to the hospital because of cranial-nerve palsies.He was in excellent health until eight days earlier, when abdominal bloating, nausea, and vomiting occurred while he was at work as a waiter. On the next day he stayed home because of continued vomiting and abdominal distress. Six days before entry he felt better, although he passed several loose stools. On the following day diplopia and dryness of the mouth developed, with dysphagia. He was seen at another hospital, where a physician found unreactive pupils and weakness of abduction of both eyes. An oral . . .
Utilization of novel highly multiplexed immunofluorescence microscopy technology to understand immunological tumor microenvironments in small cell lung carcinoma patients receiving combination PD-L1 and PARP inhibition therapy.
Authors: Christopher Julius Trindade, Elizabeth McDonough, Jeffery Hanson, Beatriz Walter Rodriguez, Nitin Roper, Billel Gasmi, Claire Roque, Makda Gebregziabher, Kris Ylaya, Patricia Fetsch, Houssein Abdul Sater, FIONA GINTY, Stephen M. Hewitt, Anish Thomas
Journal: Journal of Clinical Oncology (2019)

e14289 Background: Immune checkpoint inhibitors have changed the way we treat most malignant tumors especially lung carcinomas. While PD-L1 is the only FDA approved companion diagnostic used to predict response, its accuracy and specificity is lacking. Thus, new biomarkers and mechanisms of checkpoint inhibitor need to be elucidated. A major limitation with the current approved method, immunohistochemistry, is that it can typically only measure one parameter per tissue section. Currently new multiplexing microscopy techniques are being developed that allow us to see multiple parameters at the cell level, which can answer new questions regarding tumor immune microenvironments (TIME). In this study we used a novel multiplexed immunofluorescent (MxIF) microscopy technique, Cell DIVE™ (GE Healthcare, Issaquah, WA), to analyze formalin fixed paraffin embedded (FFPE) tissue samples from small cell lung carcinoma (SCLC) patients treated with a PD-L1 inhibitor, durvalumab (MEDI4736), in combination with a PARP inhibitor, olaparib. Methods: Biopsies from patients enrolled in a phase II expansion cohort clinical trial (NCT02484404) treated with durvalumab and olaparib were analyzed. Tumor immune response from a cohort of 3 responders and 3 non-responders, before and after treatment, underwent MxIF analysis using biomarkers including CD3, CD4, CD8, CD20, CD39, CD45RA, CD45RO, CD56, CD57, CD103, FOXP3, GATA3, LAMP1, PD-L1 and T-bet. Our panel was able to effectively discern T-cells (including subsets, maturation, and function), B-cells, and NK cells and their interaction with tumor cells. The results were validated for accuracy and consistency using immunohistochemistry and Vectra Polaris Imaging System. Results: Spatial analysis of TIME showed responders (3/3) were associated with an inflamed CD8+ T-cell tumor microenvironment while non-responders (3/3) displayed an excluded or desert CD8+ T-cell tumor microenvironment. MxIF/Cell DIVE™ allowed us to further characterize the immune response. Conclusions: Analyzing the type and pattern of immune response using multiplexed immunofluorescent and single cell characterization microscopy may better predict prognosis than PD-L1 immunohistochemistry in SCLC patients treated with immune checkpoint inhibitors. Clinical trial information: NCT02484404.
Integrating evolutionary dynamics into treatment of metastatic castrate-resistant prostate cancer (mCRPC): Updated analysis of the adaptive abiraterone (abi) study (NCT02415621).
Authors: Jingsong Zhang, Mayer N. Fishman, Joel Brown, Robert A Gatenby
Journal: Journal of Clinical Oncology (2019)

5041 Background: To achieve better prostate cancer control and to delay the emergency of treatment resistance, we developed an evolutionary game theory model using Lotka-Volterra equations with three competing prostate cancer "species": T+, Tp, and T-. T+ prostate cancer cells depend on exogenous androgen; Tp cells express CYP17A1, produce and depend on androgen; and T- cells are androgen-independent and abi-resistant. We applied this model to guide the on and off treatment cycles with abi for mCRPC. At the first interim analysis with 11 patients, this approach was shown to prolong the time to cancer progression with less than 50% drug usage compared to the conventional continuous Abi ( Nat Commun. 2017). Here we present the updated data of this phase 2 study. Methods: Men with asymptomatic or minimal symptomatic mCRPC were enrolled after they achieved &gt; 50% PSA reduction with abi as a frontline therapy for mCRPC. The primary objective is feasibility and is measured by the percentage of abi responsive men who remain to be responsive to abi (defined as &gt; 50% decline of the pre Abi PSA) after completing 2 adaptive treatment cycles. The secondary objective is to assess the clinical benefits by comparing the radiographic progression free survival (rPFS) in men undergoing adaptive Abi therapy to the historical AA 302 trial. Results: At the data cut off in Jan 2019, the study has completed enrollment for the non-African American cohort. 15 enrolled men had &gt; 11 months of follow up. All 15 men were off Abi for at least 3 months before abi was restarted for PSA progression at cycle 1. Seven out of the 15 men had completed at least 2 adaptive therapy cycles. Four of the rest 8 men remained on study and have not reached cycle 2. Six men were off study due to radiographic progression at month 11, 20.4, 30, 30.5, 38 and 53 from their first dose of Abi. Compare to the 16.2 months median rPFS in the AA 302 trial, the median rPFS of the 15 men would be no less than 30 months (p = 0.0068, Fisher’s exact test). Their average usage of Abi was 49% of the continuous Abi. Conclusions: Adaptive Abi therapy is feasible in men who responded to Abi as a frontline therapy for mCRPC. The updated data are consistent with our initial finding that our adaptive therapy approach can prolong the time to cancer progression with less than 50% drug usage compared to the conventional continuous Abi. Clinical trial information: NCT02415621.
Gene expression profiling of T-cell inflammation in small cell lung cancer.
Authors: Gareth Rivalland, Ulf Schmitz, Ramyar Molania, Chuck Bailey, Gavin Michael Wright, Alexander Dobrovic, John Rasko, Thomas John
Journal: Journal of Clinical Oncology (2019)

e20097 Background: Recent success with the use of checkpoint inhibition in SCLC has increased the importance of understanding the immunological tumour microenvironment. In many tumours gene expression profiling (GEP) of T-cell inflammation and IFN-gamma is correlated with response to checkpoint inhibitors. We present GEP results in a SCLC cohort and correlation of gene expression with IHC analysis of common checkpoints. Methods: SCLC tissue microarrays from 105 histologically confirmed SCLC specimens were scored for IHC staining of immune checkpoints on tumour and tumour infiltrating lymphocytes (TILs). A subgroup of 30 patients had sufficient tissue for GEP. Nanostring nCounter Pan-cancer immune panel, using the previously described RUVIII normalisation method, was used to examine GEP. A 28-gene IFN-G related signature was examined. Results: Median age 67y (range 53 – 86); male: 16/30 (53%); stage: limited 22/30 (73%), 5/30 (17%) extensive, 3/30 (10%) stage unknown. Significant heterogeneity was observed in gene expression. Pearson correlation co-efficients between IHC analysis and corresponding mRNA of PD-L1, PD-L2, LAG3 and TIM3, on both tumour and TILs, were not statistically significant. Significant positive correlation was found for mRNA levels of HAVCR2 (TIM3) with LAG3 and with PDCD1LG2 (PD-L2). As in the larger cohort, TIL co-expression of PD-L1, PD-L2, TIM3 and LAG3 were all associated with improved survival; med OS 89.3 v 15.7 mo; p &lt; 0.01. The cohort clustered into 4 groups with respect to the IFN-G GEP. The group with the highest level of gene expression (5/30 pts, 16.7%) had numerically improved OS; 89.3 v 21.3 mo, p = 0.23. Conclusions: In this limited cohort, gene expression did not consistently correlate with IHC. Co-ordinated expression of T-cell inflamed/IFN-G immune checkpoints occurred in 16.7% SCLC and was associated with improved survival.
Copper Transport and Disease: What Can We Learn from Organoids?
Authors: Hannah Pierson, Haojun Yang, Svetlana Lutsenko
Journal: Annual Review of Nutrition (2019)

Many metals have biological functions and play important roles in human health. Copper (Cu) is an essential metal that supports normal cellular physiology. Significant research efforts have focused on identifying the molecules and pathways involved in dietary Cu uptake in the digestive tract. The lack of an adequate in vitro model for assessing Cu transport processes in the gut has led to contradictory data and gaps in our understanding of the mechanisms involved in dietary Cu acquisition. The recent development of organoid technology has provided a tractable model system for assessing the detailed mechanistic processes involved in Cu utilization and transport in the context of nutrition. Enteroid (intestinal epithelial organoid)-based studies have identified new links between intestinal Cu metabolism and dietary fat processing. Evidence for a metabolic coupling between the dietary uptake of Cu and uptake of fat (which were previously thought to be independent) is a new and exciting finding that highlights the utility of these three-dimensional primary culture systems. This review has three goals: ( a) to critically discuss the roles of key Cu transport enzymes in dietary Cu uptake; ( b) to assess the use, utility, and limitations of organoid technology in research into nutritional Cu transport and Cu-based diseases; and ( c) to highlight emerging connections between nutritional Cu homeostasis and fat metabolism.
PAM50 HER2-enriched subtype as an independent prognostic factor in early-stage HER2+ breast cancer following adjuvant chemotherapy plus trastuzumab in the ShortHER trial.
Authors: Pier Franco Conte, Gaia Griguolo, Maria Vittoria Dieci, Giancarlo Bisagni, Alba Ariela Brandes, Antonio Frassoldati, Luigi Cavanna, Antonino Musolino, Francesco Giotta, Anita Rimanti, Ornella Garrone, Patricia Galvan, Fara Brasó Maristany, Enrico Orvieto, Loredana Urso, Antonino Maiorana, Sara Balduzzi, Roberto D'Amico, Valentina Guarneri, Aleix Prat
Journal: Journal of Clinical Oncology (2019)

544 Background: We investigated the prognostic role of the PAM50 HER2-enriched (HER2-E) subtype in HER2+ early breast cancer enrolled in the randomized Phase III ShortHER trial. Methods: The ShortHER study randomized 1254 HER2+ early breast cancer patients to receive 9 weeks vs 1 year of adjuvant trastuzumab combined with chemotherapy. Gene expression measured using nCounter platform was available for 438 surgical samples. Intrinsic subtyping was determined using the research-based PAM50 predictor. Metastasis-free survival (MFS) was calculated from randomization to distant disease recurrence or death (median follow up 72 months). Uni- and multi-variable analysis were performed using Cox models. Results: PAM50 subtype distribution was: HER2-E 53% (N = 233), Luminal A 20% (N = 87), Luminal B 10% (N = 43), Normal-like 11% (N = 48) and Basal-like 6% (N = 27). HER2-E subtype was associated with hormone receptor-negative status (p &lt; 0.001) and TILs ≥20% (p &lt; 0.001), but not with stage and age ( &lt; or ≥60 yrs). HER2-E subtype was associated with worse MFS vs other PAM50 subtypes overall (HR 2.78, p = 0.001), in the short (HR 2.24, p = 0.046), and in the long arm (HR 4.04, p = 0.011). Multivariable Cox model confirmed the independent prognostic value of HER2-E subtype (Table). HER2-E subtype added significant prognostic value on top of clinicopathological variables (Likelihood ratio test p &lt; 0.001). Conclusions: HER2-E intrinsic subtype is an independent prognostic factor for HER2+ early breast cancer patients treated with adjuvant chemotherapy and trastuzumab. Integration of PAM50 subtype in prognostic algorithms can help refine risk stratification. These findings warrant independent validation. Clinical trial information: NCT00629278. [Table: see text]
mTORC2 Suppresses GSK3-Dependent Snail Degradation to Positively Regulate Cancer Cell Invasion and Metastasis
Authors: Shuo Zhang, Guoqing Qian, Qian-Qian Zhang, Yuying Yao, Dongsheng Wang, Zhuo G. Chen, Li-Jing Wang, Mingwei Chen, Shi-Yong Sun
Journal: Cancer Research (2019)

mTOR complex 1 (mTORC1) positively regulates cell invasion and metastasis by enhancing translation of Snail. A connection between mTOR complex 2 (mTORC2) and cell invasion and metastasis has also been suggested, yet the underlying biology or mechanism is largely unknown and thus is the focus of this study. Inhibition of mTOR with both mTOR inhibitors and knockdown of key components of mTORC, including rictor, Sin1, and raptor, decreased Snail protein levels. Inhibition of mTOR enhanced the rate of Snail degradation, which could be rescued by inhibition of the proteasome. Critically, inhibition of mTORC2 (by knocking down rictor) but not mTORC1 (by knocking down raptor) enhanced Snail degradation. Therefore, only mTORC2 inhibition induces Snail proteasomal degradation, resulting in eventual Snail reduction. Interestingly, inhibition of GSK3 but not SCF/β-TrCP rescued the Snail reduction induced by mTOR inhibitors, suggesting GSK3-dependent, but SCF/β-TrCP-independent proteasomal degradation of Snail. Accordingly, mTOR inhibitors elevated E-cadherin levels and suppressed cancer cell migration and invasion in vitro and metastasis in vivo. Collectively, this study reveals that mTORC2 positively regulates Snail stability to control cell invasion and metastasis. SIGNIFICANCE: These findings delineate a new regulation mechanism of Snail, an important master regulator of epithelial-mesenchymal transition and invasion in cancers.
Selective and nonselective GR antagonists in combination with chemotherapy in ovarian cancer PDX models.
Authors: Jennifer Taylor Veneris, Xiaonan Hou, S. John Weroha, Ethan P. Heinzen, Matthew John Maurer, Ann L. Oberg, Suzanne D. Conzen, Gini F. Fleming
Journal: Journal of Clinical Oncology (2019)

e17039 Background: Treatment strategies are needed for platinum-resistant recurrent ovarian cancer. Glucocorticoid receptor (GR) is associated with poor prognosis in ovarian cancer. GR signaling inhibits chemotherapy-induced cell death via transcriptional regulation of anti-apoptotic proteins. Non-selective (mifepristone) and selective GR antagonists (Relacorilant, Corcept Therapeutics) are under clinical development (eg. NCT02046421, NCT03776812). We hypothesized that GR antagonism would improve chemotherapy sensitivity in ovarian cancer patient-derived xenograft (PDX) models. Methods: Five PDX models were selected based on GR expression above median RNA seq levels. Tissues were transplanted into 300 female SCID-Bg mice at the Mayo Clinic. Once tumor diameter reached 0.2 cm, mice were randomized into treatment arms (2-25 mice per arm) and treated intraperitoneal (i.p): control (9% saline, CTL) on day 0 (D0), 1, 7, 8, 14, 15, 21, 22; mifepristone (MIF), 15 mg/kg D0, 1, 7, 8, 14, 15, 21, 22; relacorilant (134), 20 mg/kg D0, 1, 7, 8, 14, 15, 21, 22; carboplatin (CBDCA) at the MTD, 51 mg/kg D1, 8, 15, 22; CBDCA + MIF; CBDCA + 134. Tumor area was measured by ultrasound weekly (D0-D28), and the ratio calculated relative to D0. Tumor growth curves were compared between arms for each PDX via a linear mixed effects regression test of coincident curves. Time to progression was also evaluated and will be presented. Results: In 1/5 models (PH160), CBDCA + MIF significantly suppressed tumor growth compared to CBDCA alone (p &lt; 0.05, Table 1). Addition of 134 to CBDCA did not suppress tumor growth compared to CBDCA alone in any model. In the 2 models with no difference of CBDCA versus CTL (PH160, PH454), addition of a GR antagonist to CBDCA suppressed tumor growth versus CTL. Conclusions: Addition of GR antagonists can improve response to chemotherapy. Work is ongoing to identify the GR transcriptional network, tumor, and host characteristics which predict responses to GR antagonists. [Table: see text]