tbuckley/cabot-search huggingface dataset:
Optimizing the program of sequential chemotherapy for advanced gastric cancer based on gene-level CNVs called from ctDNA.
Authors: Wenqi Xi, Chenfei Zhou, Shouwei Zhang, Zhao Yi, Yawei Chen, Jun Ji, Tao Ma, Junwei Wu, Chengfang Shangguan, Zhenggang Zhu, Jun Zhang
Journal: Journal of Clinical Oncology (2021)

e16068 Background: Tumor evolutionary trade-offs under treatment pressure can be utilized to optimize therapy. We aimed to profile the dynamic pattern of gene-level copy number variations (CNVs) for advance gastric cancer (GCA) patients who underwent sequential chemotherapy and optimized the therapy program. Methods: 27 chemo-naive advanced GCA patients with distant metastasis were enrolled. Peripheral blood samples were collected at different time points, including pre-therapy and disease progression on a specific regimen. Gene-level CNVs were called from ctDNA of blood samples and drug modified score (DMS) was defined as the ratio of CNV value between samples of pre- and post-treatment for each gene. Positive and negative DMS of a gene represented its resistance and sensitivity to a selected regimen, respectively. Then, the best initial regimen was selected and the optimal program of sequential chemotherapy was designed for each patient. Results: DMS of gene was calculated for four chemotherapy regimens, including platinum-based doublet regimen (Pt-2d), oral-fluorouracil prodrug (O-FP), paclitaxel-based regimen (PTX) and irinotecan-based regimen (CPT-11). Based on DMS distribution, resistant and sensitive genes were determined for each regimen through a heuristic method. Functional enrichment analysis showed that resistant genes mainly involved in cellular response to oxygen-containing compound and regulation of cell proliferation, while sensitive genes mainly involved in positive regulation of macromolecule biosynthetic process and regulation of apoptotic process. Then, drug resistant score (DRS, defined as DMS weighted sum of CNV values of resistant genes) was calculated and the regimen with the lowest DRS was selected as the best initial treatment for each patient. The best initial treatment of 16 patients was CPT-11, of 8 patients was O-FP, of 2 patients was Pt-2d and of 1 patient was PTX. Following that, the optimal program of sequential chemotherapy was designed according to the percentage of shared resistant genes between regimens for each patient, where two regimens with the lowest percentage were recommended to use one by one. Finally, prognostic analysis showed that differences between the optimal and practical program of sequential chemotherapy were negatively correlated to overall survival of patients. Conclusions: Based on gene-level CNVs called from ctDNA of blood samples, we determined the best initial treatment and designed the optimal program of sequential chemotherapy for advanced GCA patients, pacing a key step toward precision medicine in GCA field.
Detection of FGFR fusions in intrahepatic cholangiocarcinoma using targeted RNA sequencing.
Authors: Maria Farooq, Havell Markus, Bradon McDonald, Jan B. Egan, Tania Contente-Cuomo, Ahuva Odenheimer, Martin Fernandez-Zapico, Mitesh J. Borad, Muhammed Murtaza
Journal: Journal of Clinical Oncology (2021)

e16185 Background: Comprehensive sequencing efforts have identified fibroblast growth factor receptor (FGFR) translocations in numerous cancers. FGFR2 fusions were recently identified as an actionable therapeutic target in ̃17% of cholangiocarcinoma patients, predominantly found in patients with intrahepatic cholangiocarcinoma. Genomic partners for FGFR fusions are variable. In addition, obtaining high yield tissue biopsies for CCA remains challenging and tumor tissue available for molecular analyses is scarce. When combined, these two factors make detection of FGFR fusions in CCA challenging. An accurate molecular assay to detect FGFR fusions in CCA could improve utilization of FGFR-targeted therapies. Methods: The objective of our study was to develop an approach for targeted RNA analysis to improve sensitivity for FGFR fusion detection from limited tumor material. We adapted the sensitive targeted digital sequencing (TARDIS) approach recently developed in our lab for analysis of RNA. This approach utilizes a combination of open-ended targeted amplification followed by ligation, enabling detection of tyrosine kinase fusions without prior knowledge of the precise sequence of the fusion breakpoint or identity of the fusion partner. For evaluation of analytical performance, we analyzed RNA from a CCA organoid model with a known FGFR2 fusion, and Seraseq Fusion RNA Mix v3 Reference Material with two known FGFR3 fusions. Results: Without prior knowledge the partner or coordinates of the fusion breakpoint, we detected an FGFR2-KIF5C fusion in RNA from a CCA organoid model. The fusion breakpoint coordinates predicted by TARDIS-RNA were validated by comparison with RNA-Seq. To assess sensitivity and quantitative performance of the assay, we analyzed a serial dilution of the reference RNA sample from Seraseq with concentration of RNA molecules representing candidate fusions verified by digital PCR. Using TARDIS-RNA to analyze replicates with 5 ng RNA input, we were able to detect candidate fusions represented by as few as 2.7 fusion molecules on average. Concentrations of fusion molecules measured using the two methods were highly correlated (R = 0.96). Conclusions: These results demonstrate sensitivity and quantitative performance of a targeted RNA sequencing assay to detect and quantify FGFR fusions in tumor specimen from intrahepatic cholangiocarcinoma. On-going work is focused on further evaluating assay performance and characterizing FGFR fusions using additional tissue specimen.
NIR-II fluorescence imaging guided tumor-specific NIR-II photothermal therapy enhanced by starvation mediated thermal sensitization strategy
Authors: Yeneng Dai, Zhiquan Sun, Honghai Zhao, Dashan Qi, Xiangyu Li, Diya Gao, Meixing Li, Quli Fan, Qingming Shen, Wei Huang
Journal: Biomaterials (2021)
Simplified lymphatic microsurgical preventing healing approach (SLYMPHA) for the prevention of breast cancer-related lymphedema after axillary lymph node dissection.
Authors: Tolga Ozmen, Christina Layton, Orli Friedman Eldar, Siarhei Melnikau, Susan Kesmodel, Eli Avisar
Journal: Journal of Clinical Oncology (2021)

e12581 Background: Lymphedema (LE) is a serious complication of axillary lymph node dissection (ALND) with an incidence rate of 16%. Simplified Lymphatic Microsurgical Preventing Healing Approach (SLYMPHA) is a safe and relatively simple method, which decreases incidence of LE dramatically. Our initial study showed an 88% decrease in clinical LE rate. In the initial study, we used arm circumference measurement for the diagnosis of LE and median follow up was 15 months. The aim of this study was to confirm these results after a long-term follow up period and by using bioimpedance spectroscopy (L-Dex) technology in detecting LE. Methods: All patients, undergoing ALND with or without SLYMPHA between January 2014 and November 2020 were included in the study. Patients with no postoperative L-Dex measurements were excluded. A L-Dex score outside the normal range (± 10 L-Dex unit) or &gt;10 L-Dex unit increase above patient’s baseline was considered as LE. The incidence of LE was compared between patients with and without SLYMPHA. Results: 194 patients were included in the study. 57% of cohort underwent SLYMPHA. Mean follow-up time was 47 ±37 months. Patients, who underwent SLYMPHA, had a significantly lower rate of LE (16% vs 32%; p=0.01; OR 0.4 [0.2-0.8]). Conclusions: SLYMPHA is a safe and relatively simple method, which continued its efficacy after a long-term follow up period. It should be considered as an adjunct procedure to ALND for all patients during initial surgery. [Table: see text]
A simulation-based evaluation of machine learning models for clinical decision support: application and analysis using hospital readmission
Authors: Velibor V. Mišić, Kumar Rajaram, Eilon Gabel
Journal: npj Digital Medicine (2021)

Abstract The interest in applying machine learning in healthcare has grown rapidly in recent years. Most predictive algorithms requiring pathway implementations are evaluated using metrics focused on predictive performance, such as the c statistic. However, these metrics are of limited clinical value, for two reasons: (1) they do not account for the algorithm’s role within a provider workflow; and (2) they do not quantify the algorithm’s value in terms of patient outcomes and cost savings. We propose a model for simulating the selection of patients over time by a clinician using a machine learning algorithm, and quantifying the expected patient outcomes and cost savings. Using data on unplanned emergency department surgical readmissions, we show that factors such as the provider’s schedule and postoperative prediction timing can have major effects on the pathway cohort size and potential cost reductions from preventing hospital readmissions.
EPCT-19. DRUG RESISTANCE IN MEDULLOBLASTOMA ADDRESSED WITH OLIG2 INHIBITOR, CT-179
Authors: Taylor Dismuke, Chaemin Lim, Timothy Gershon
Journal: Neuro-Oncology (2021)

Abstract Patients with medulloblastoma, the most common malignant pediatric brain tumor. need improved treatment options. Conventional medulloblastoma treatment, with resection, chemotherapy, and radiation, leaves survivors at risk of neurocognitive injury, growth defects, and psychosocial impairment. Moreover, there is no effective therapy for recurrent medulloblastoma. We seek to identify novel treatments that will address systemic toxicity and tumor recurrence. We tested a nanoparticle formulation of the CDK4/6 inhibitor, palbociclib (POx-palbo) in mice genetically-engineered to develop medulloblastoma (G-Smo mice) and found a significant anti-tumor effect that was consistently limited by the recurrence of OLIG2+ medulloblastoma stem cells. We then tested the hypothesis that directly targeting OLIG2 function would improve the efficacy of palbociclib and forestall resistance. We therefore examined the potential efficacy of CT-179, a first-in-class OLIG2 inhibitor, in G-Smo mice engineered to express luciferase as an SHH reporter. These studies showed that CT-179 decreased SHH signaling and prolonged event-free survival. Pharmacodynamic studies of G-Smo mice during treatment showed that CT-179 alters cell-cycle progression and promotes a shift towards cell-cycle arrest. Mechanistically, CT-179 decreased the Olig2 phosphorylation. The combination of CT-179 and POx-palbo increased event-free survival of G-Smo mice compared to either agent administered alone. Our studies show both the potential of the palbociclib CT-179 combination, and the potential for CT-179 to improve the efficacy of therapies limited by OLIG2+ stem cell recurrence. As OLIG2+ stem cells have been shown to drive recurrence to conventional therapy and OLIG2 phosphorylation disables p53-driven apoptosis, CT-179 may be a versatile agent to enhance both targeted and cytotoxic treatments.
Error in Figure.
Authors: M. Arthur, N. M. Fett, E. Latour, H. Jacobe, E. Kunzler, S. Florez-Pollack, J. Houser, S. Sharma, S. Prasad, A. Femia, M. J. Stern, L. K. Pappas-Taffer, R. Gaffney, A. P. Fernandez, D. Knabel, A. R. Cardones, N. Leung, A. Laumann, J. M. Yu, J. Zhao, R. A. Vleugels, E. Tkachenko, K. Lo
Journal: JAMA Dermatology (2021)
Biomarker-oriented study of durvalumab in combination with olaparib and paclitaxel in gastric cancer: A phase 2 trial-in-progress.
Authors: Tae Yong Kim, Jee Sun Yoon, Ah-Rong Nam, Ju-Hee Bang, Kyoung Seok Oh, Hye-Rim Seo, Jae-Min Kim, Do-Youn Oh
Journal: Journal of Clinical Oncology (2021)

TPS4153 Background: Olaparib (PARP inhibitor) leads to DNA damage and cell death. In phase III study (GOLD), olaparib plus paclitaxel did not improve overall survival (OS) compared with paclitaxel in second-line gastric cancer (GC) patients with statistical significance, even though there was absolute increase of OS (Lancet Oncol 2017). This highlights the importance of biomarker-based patient selection. The changes of tumor microenvironment by paclitaxel/olaparib have not been explored. Besides DNA damage, olaparib induces positive or negative immune modulation by recruiting T cells, promoting type I interferon and upregulating PD-L1, which suggests anti-PD (L1) inhibitor plus olaparib could enhance anti-tumor immunity. Combination of Anti-PD-1 agents with chemotherapy showed a good clinical efficacy in first-line of GC compared with chemotherapy alone (Checkmate 649). Based on these findings, the combination of paclitaxel/olaparib/anti-PD(L1)1 inhibitor, with different mode of actions, might enhance antitumor activity. This is phase II study of paclitaxel/olaparib/durvalumab combination in second-line GC patients, to find out immune modulation effects by paclitaxel/olaparib combination, and to see the efficacy, safety, optimal biomarkers for this combination. Methods: All patients with histologically confirmed unresectable GC have failed to prior one chemotherapy and measurable lesion. Prior exposure to anti-PD(L1)1, PARP inhibitor is excluded. At 1st cycle, paclitaxel (80 mg/m 2 ) on D1, 8 and 15 and olaparib (150 mg bid) on D1-28 is administered. Pre-treatment biopsy and after first cycle biopsy is done. From second cycle, durvalumab 1500 mg on D1 every 4 weeks is added. At the time of disease progression, tumor biopsy is mandatory. Blood samples for biomarkers should be obtained every cycles. Response evaluation is performed after first 3 cycles and repeated every 2 cycles. Primary endpoint is the disease control rate (the percentage of patients who have achieved complete or partial remission, stable disease based on RECIST v1). Key secondary endpoints are overall response rate, progression-free survival, OS, quality of life and safety. Clinical trial information: NCT03579784.
Engineering circular RNA regulators to specifically promote circular RNA production
Authors: Yangfan Qi, Wei Han, Dan Chen, Jinyao Zhao, Lu Bai, Fang Huang, Zhenwei Dai, Gang Li, Chaoqun Chen, Wenjing Zhang, Jinrui Zhang, Bilian Jin, Yang Wang
Journal: Theranostics (2021)

Background: A large number of circular RNAs (circRNAs) have been discovered in the mammalian transcriptome with high abundance, which play vital roles in gene regulation, thereby participating in the development of multiple diseases. However, the biogenesis, regulation, and especially manipulation of circRNAs still remain largely unknown. Methods: Engineering circRNA regulators (ECRRs) were developed to promote circRNA biogenesis. Multiple circRNA mini-gene reporters were generated to evaluate the regulatory role of ECRRs. RT-PCR, qRT-PCR, northern blot, western blot, and flow cytometry assays were applied to assess the efficiency of artificial circRNA regulators on circRNA production in the presence or absence of RNase R treatment. Results: We engineered circRNA regulators by combining sequence-specific RNA binding motifs of human Pumilio 1 with functional domains that could form dimerization. We applied these engineered regulators to promote the circRNA production of the exogenous circRNA minigene reporter circGFP, thereby stimulating the functional GFP protein generation. Crucially, such regulation is in time-course dependent and dose-dependent manners with designed specificity. Moreover, the application of ECRRs could also stimulate circRNA biogenesis of another minigene reporter circScreen, suggesting that ECRRs can be commonly used to promote circRNA generation of exogenous reporters. Most importantly, ECRRs could be utilized to specifically promote the production of the endogenous circRNAs circ10720 and circBIRC6 as well. Conclusion: Our approach allows the creation of engineered regulators to target virtually any pre-mRNA in vivo, offering a novel avenue to investigate circRNA biogenesis and manipulate disease-related circRNA production.
Chilblains-like Nonischemic Eruption During the COVID-19 Pandemic—Distinct Features in Adolescents
Authors: Farzam Gorouhi
Journal: JAMA Network Open (2021)

Valentina Discepolo, MD, PhD; Andrea Catzola, MD; Luca Pierri, MD; Massimo Mascolo, MD, PhD; Francesca Della Casa, MD; Maria Vastarella, MD; Grace Smith, BS; Antonio Travaglino, MD; Alessandra Punziano, MD; Paola Nappa, MD; Stefania Staibano, MD; Eugenia Bruzzese, MD; Gabriella Fabbrocini, MD; Alfredo Guarino, MD; Maria Alessio, MD
Psychosocial impacts of the COVID-19 pandemic on young adult cancer survivors and parents of children with cancer.
Authors: Stephanie M Smith, Dhanya Kumar, Catherine Benedict, Lauren C. Heathcote, Catherine Aftandilian, Melissa Bondy, Lidia Schapira
Journal: Journal of Clinical Oncology (2021)

10050 Background: The COVID-19 pandemic has affected oncology practice in a variety of ways. We sought to evaluate the impact on pediatric oncology parent and young adult (YA) patient experiences, concerns, and perceived stress. Methods: We conducted a cross-sectional Internet-based survey of parents and YA patients in the pediatric oncology and survivorship clinics at Stanford between June-December 2020. Patients were recruited in person by clinic staff or through the electronic patient health portal. Surveys (available in English and Spanish) included the NIH Perceived Stress Scale (PSS-10) and investigator-developed questions evaluating clinical practice changes, concerns about health and cancer care, and pandemic-related challenges. Bivariate analyses evaluated associations between demographic, clinical, and pandemic-related factors and (a) concern about the pandemic affecting health and cancer care, and (b) perceived stress. Results: Among 81 participants (66 parents, mean age 41.6 ± SD 9.6; 15 YAs, mean age 21.9 ± 8.4 years), 37% self-identified as Hispanic/Latino, 36% non-Hispanic white, and 21% Asian. Twenty-eight percent were on treatment and 47% had completed treatment (79% &lt; 5 years prior). Thirty percent reported cancer-related appointment changes, largely rescheduling (75%) and/or switching to telehealth (42%). Nearly half (45%) of parents and 27% of YAs reported feeling ‘very’ or ‘extremely’ concerned about the pandemic affecting their child’s/their health or cancer care. Race/ethnicity emerged as the only demographic feature that was significantly associated with high concern (p = 0.018), with 57% of Hispanic/Latino and only 21% of non-Hispanic white respondents reporting high levels of concern. Specific concerns included fear of severe infection, immunosuppression, and whether infection would change treatment and compromise effectiveness. Parents and YAs reported ‘a lot’ or ‘a great deal’ of challenges in their personal/family life (61%) and work/professional life (48%). Among these were having less support from friends/family (35%), reduced wages/work hours (31%), and job loss (20%) with 20% reporting ≥ 3 challenges. On the PSS-10, stress in the past month was high for parents (mean 30 ± 4) and YAs (mean 31 ± 5.1) on a scale of 0-40. Risk factors for higher stress included: male gender (p = 0.028), less support from family/friends (p = 0.002), and experiencing ≥ 3 pandemic-related challenges (p = 0.013). Conclusions: Our findings confirm the prevalent worry and stress that pediatric oncology patients and families are experiencing during the COVID-19 pandemic. Better communication about cancer care service changes may help to alleviate some concerns. Supportive care resources may also help patients and families cope with psychosocial stressors, particularly among at-risk groups.
Development and validation of a prediction model for kidney failure in long-term survivors of childhood cancer: A report from the Childhood Cancer Survivor Study (CCSS).
Authors: Natalie Lucy Wu, Yan Chen, Bryan V. Dieffenbach, Nan Li, Matthew J. Ehrhardt, Daniel M. Green, Sangeeta Hingorani, Rebecca M. Howell, John L. Jefferies, Daniel A. Mulrooney, Kevin C. Oeffinger, Leslie L. Robison, Brent R. Weil, Yan Yuan, Yutaka Yasui, Melissa M. Hudson, Wendy M. Leisenring, Gregory T. Armstrong, Eric Jessen Chow
Journal: Journal of Clinical Oncology (2021)

10047 Background: Kidney failure (need for dialysis or kidney transplantation, or death due to kidney disease) is a rare but serious late effect for survivors of childhood cancer. We aimed to develop a model using demographic and treatment characteristics to predict individual risk of kidney failure among five-year survivors of childhood cancer. Methods: CCSS survivors without kidney failure at five years after cancer diagnosis (n = 25,483) were assessed for subsequent kidney failure by age 40. Outcomes were self-reported and corroborated by the Organ Procurement and Transplantation Network and the National Death Index. A sibling cohort (n = 5045) served as a comparator. Piecewise exponential models with backward selection estimated the relationships between potential predictors and kidney failure and were converted to integer risk scores. Additional results from the St. Jude Lifetime Cohort Study (SJLIFE, n = 2490) and the National Wilms Tumor Study (NWTS, n = 6760) validated the models. Results: Among CCSS survivors, 204 developed late kidney failure. We developed a model with sex, race/ethnicity, age at cancer diagnosis, nephrectomy, exposure to specific chemotherapy, any abdominal radiation, presence of genitourinary anomalies, and early-onset hypertension (Table). Risk scores achieved an area under the curve (AUC) and concordance (C) statistic of 0.65 and 0.68 for kidney failure by age 40. Validation cohort AUC and C statistics were 0.83/0.86 for SJLIFE (8 cases) and 0.61/0.63 for NWTS (91 cases). An alternative model with specific chemotherapy doses and kidney-specific radiation dosimetry had similar AUC and C statistic (0.67/0.70). Integer risk scores were collapsed to form statistically distinct low (score &lt;3; 87 cases of 17,326), moderate (score 3-5; 63 cases of 4667), and high (score 6+; 18 cases of 401) risk groups. These groups corresponded to cumulative incidences in CCSS of kidney failure by age 40 of 0.6% (95% CI 0.4-0.7%), 2.3% (95% CI 1.6-3.2%), and 9.4% (95% CI 4.4-16.7%), compared with 0.2% (95% CI 0.1-0.5%) among siblings. Conclusions: Using readily available information, we were able to identify low, moderate, and high risk groups for developing kidney failure following treatment for childhood cancer. These prediction models may help guide screening and interventional strategies for higher risk survivors.[Table: see text]