tbuckley/cabot-search huggingface dataset:
Vitamin D receptor gene polymorphisms, bioavailable 25-hydroxyvitamin D, and hepatocellular carcinoma survival
Authors: Jing Shu, Mingjie Zhang, Xiaocong Dong, Jingan Long, Yunshan Li, Peishan Tan, Tongtong He, Edward L Giovannucci, Xuehong Zhang, Zhongguo Zhou, Yanjun Xu, Xiaojun Xu, Tianyou Peng, Jialin Lu, Minshan Chen, Huilian Zhu, Yaojun Zhang, Aiping Fang
Journal: JNCI Journal of the National Cancer Institute (2024)

Little is known about the role of vitamin D receptor polymorphisms and their interaction with vitamin D status in hepatocellular carcinoma (HCC) prognosis. We evaluated the association of TaqI, BsmI, Cdx-2, and ApaI polymorphisms, individually and in combination, with liver cancer-specific (LCSS) and overall survival (OS) among 967 patients with newly diagnosed HCC. Subsequently, we examined whether these polymorphisms modified the association between serum bioavailable 25-hydroxyvitamin D (25OHD) concentrations and survival. Cox proportional hazard models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs). During a median follow-up of 1017 days, 393 deaths occurred, with 360 attributed to HCC. Having TaqI G allele (HRper allele = 1.30, 95% CI = 1.08 to 1.57) or BsmI T allele (HRper allele = 1.41, 95% CI = 1.01 to 1.99) was associated with worse LCSS. Carrying increasing numbers of protective alleles was associated with superior LCSS (HR6-8 vs 0-3 = 0.52, 95% CI = 0.34 to 0.80). The inverse association of bioavailable 25OHD with LCSS was statistically significant only in patients with TaqI AA (HRQuartile 4 vs Quartile 1 = 0.63, 95% CI = 0.44 to 0.92), BsmI CC (HRQuartile 4 vs Quartile 1 = 0.62, 95% CI = 0.44 to 0.88), and 6 to 8 protective alleles (HRQuartile 4 vs Quartile 1 = 0.45, 95% CI = 0.23 to 0.87). Similar associations were observed for OS. Patients carrying wild-type TaqI, BsmI, or more protective alleles had improved survival and might benefit from optimizing bioavailable 25OHD status.
Developing a deep learning algorithm to support decision making for the classification of microsatellite instability (MSI) in cancer, using artificial intelligence(AI).
Authors: Maria Teresa Pombo, Julieta Chirkes, Andrea Erbetti, Olivia Sanguinetti, Adrian Perez, Federico Paschetta, Juan Manuel O'Connor, Ana Gorodisch
Journal: Journal of Clinical Oncology (2024)

11152 Background: Digital pathology (DP) is an image-based environment, which allows the acquisition, and interpretation of pathological information from a digitized slide. The objective of this work was to build an AI model for predicting MSI in endometrial, colorectal, and gastric carcinomas, to simplify laboratory processes, in a developing country. Nowadays, it is crucial to recognize patients who will respond to treatments such as immunotherapy. Methods: The computational tool utilized was CLAM (clustering-constrained-attention multiple instance learning). This architecture developed by Lu et al. is a deep learning method that utilizes weak supervision and attention based learning, to identify the most relevant regions for tumor classification, in whole slide images (WSI). CLAM was designed to excel in tumor subtyping tasks which are discernible to human visual perception. We are challenging this architecture by employing it in the detection of a molecular phenomenon. For training and internal evaluation, images from TCGA and CPTAC were obtained for endometrial cancer (EC). For colorectal (CCR) and gastric cancer (GC), only images from TCGA. Archived histological samples with MSI/MMR status from a donor lab , were used for external validation. Results: Tests conducted on an internal cohort of 58 samples for CCR and GC revealed a sensitivity of 76.9%, a specificity of 78.1%, and an AUC-ROC of 76.3%. In the case of EC, where 38 cases were evaluated, the sensitivity was 100%, specificity was 68%, and AUC-ROC reached 92%. Notably, regarding the externalcohort consisting of 109 samples, both models demonstrated a high sensitivity of up to 90% in recognizing positive cases. Due to the models’ specificity (approximately 45%), it was not possible to accurately predict MSS samples in all three types of tumors. Conclusions: Promising results were obtained for the first approach in detecting molecular biology events, such as MSI, using AI. CLAM is a useful platform for digital pathology, but new validations are needed to enhance our work and strengthen the model. It is hypothesized that CLAM may not be the best tool for AI in identifying molecular biology events, so other directions are being explored. For external cohorts, preanalytical changes play an important role in obtaining accurate results with scanners and digitalization. It is crucial to teach healthcare professionals about AI in order to ensure its availability, in every diagnostic laboratory.
Clinical efficacy and safety of mTOR inhibitor in patients with advanced unresectable epithelioid hemangioendothelioma (EHE).
Authors: Huijing Tan, Yuting Sun, Yihebali Chi
Journal: Journal of Clinical Oncology (2024)

e23540 Background: Epithelioidhemangioendothelioma is a rare vascular soft tissue sarcoma, 90% of which contains WWTR1-CAMTA1 fusion gene. Studies have shown that mTOR inhibitors may have a certain effect on EHE patients. Methods: A retrospective analysis of the efficacy and safety of mTOR inhibitor everolimus in the treatment of advanced unresectable epithelioidhemangioendothelioma in our hospital in the past one year. Patients with advanced epithelioidhemangioendothelioma (EHE) confirmed by consultation in the pathological center received this regimen, everolimus 10mg, once a day orally for 28 days, every 4 weeks as a treatment cycle until the disease progressed or showed intolerable toxicity. Results: There were 3 females and 5 males, and their average age was 41.8 years old. All of them were unresectable with liver, lung, and shoulder primary lesions, and lungs, liver, pleura and bone metastasis. Ki67 is from 2% to 10%. 3 patients who received molecular pathological examination were all identified the WWTR1-CAMTA1 fusion gene, and one of them also had EWSR1 chromosome translocation. Previous antineoplastic treatments included gemcitabine, cisplatin, albumin paclitaxel, epirubicin, dacarbazine chemotherapy, anlotinib targeting, and toripalimab immune therapy. 5 patients were treated with first-line drugs, 2 cases with second-line and 1 case with third-line. In terms of overall efficacy, 1 case was not evaluated, 2 cases lost follow-up due to poor tolerance and economic factors, 2 cases were included in the clinical trails after reaching tumor control for 3 months, and the other 3 cases achieved tumor remission with a median PFS of 11.0 months, and the best curative effect was SDa. Severe oral mucositis can greatly affect the medication experience of patients, which can be relieved after symptomatic medication, or when interstitial pneumonia and hemogram decrease significantly, we can consider the oral administration of everolimus 5mg. Conclusions: At present, there is no standard treatment for EHE, we can roughly see the efficacy of mTOR inhibitor everolimus in some EHE patients, mainly disease stability. Emphasis on side effect management, improve tolerance, and systematic treatment of EHE needs to be further explored.
APIR: Aggregating Universal Proteomics Database Search Algorithms for Peptide Identification with FDR Control
Authors: Yiling Elaine Chen, Xinzhou Ge, Kyla Woyshner, MeiLu McDermott, Antigoni Manousopoulou, Scott B Ficarro, Jarrod A Marto, Kexin Li, Leo David Wang, Jingyi Jessica Li
Journal: Genomics Proteomics & Bioinformatics (2024)

Advances in mass spectrometry (MS) have enabled high-throughput analysis of proteomes in biological systems. The state-of-the-art MS data analysis relies on database search algorithms to quantify proteins by identifying peptide-spectrum matches (PSMs), which convert mass spectra to peptide sequences. Different database search algorithms use distinct search strategies and thus may identify unique PSMs. However, no existing approaches can aggregate all user-specified database search algorithms with a guaranteed increase in the number of identified peptides and a control on the false discovery rate (FDR). To fill in this gap, we proposed a statistical framework, Aggregation of Peptide Identification Results (APIR), that is universally compatible with all database search algorithms. Notably, under an FDR threshold, APIR is guaranteed to identify at least as many, if not more, peptides as individual database search algorithms do. Evaluation of APIR on a complex proteomics standard dataset showed that APIR outpowers individual database search algorithms and empirically controls the FDR. Real data studies showed that APIR can identify disease-related proteins and post-translational modifications missed by some individual database search algorithms. The APIR framework is easily extendable to aggregating discoveries made by multiple algorithms in other high-throughput biomedical data analysis, e.g., differential gene expression analysis on RNA sequencing data. The APIR R package is available at https://github.com/yiling0210/APIR.
Medicare reimbursement trends of biological reference agents and their biosimilars.
Authors: John Albaugh, Puneeth Indurlal
Journal: Journal of Clinical Oncology (2024)

11155 Background: Biosimilars have the potential to reduce healthcare costs for payers and provide savings to patients by introducing competition and driving down prices. Centers for Medicare and Medicaid Services’ (CMS) Average Sales Price (ASP) is used as an index price to determine Medicare drug reimbursement (MCR) in the United States and is published on a quarterly basis. We studied the trends of ASP and MCR reimbursement rates for reference and biosimilar agents. Methods: Using publicly available quarterly CMS data, we evaluated and compared the trends of MCR for 7 reference and 25 biosimilar agents for a period of 2 years before and 5 years after launch. We evaluated the MCR for filgrastim, pegfilgrastim, bevacizumab, trastuzumab, rituximab, infliximab, epoetin-alfa, and their respective biosimilars. Results: On average, the published MCR for all reference agents increased by 9.2% (range: 0.6% to 16.8%) over the 2-year period prior to the biosimilar launch. Over the 5-year period following the launch of the first biosimilar, reference agents’ MCR fell 32.7% (range: -8.0% to -78.0%) while biosimilar agents’ MCR fell 50.3% (range: -3.7% to -90.5%) over the same period, with a median follow-up period of 16 quarters. Biosimilar MCR rates fell at an accelerated rate compared to reference agents. 76% (19 of 25) of the biosimilars that entered the market had an initial MCR below, and 20% (5 of 25) above, that of the reference agent. 16 of 18 successive biosimilars for reference agents launched with a MCR above that of the first biosimilar. Despite the fall in MCR, reference agents’ rates in the most recent quarter were 2x higher than their corresponding biosimilar agents, except for pegfilgrastim, which had a precipitous fall in MCR (87%) after biosimilar launch to a price lower than 5 of its 6 biosimilars. Conclusions: Biosimilars, with lower Medicare reimbursement at launch, and an accelerated decline in ASP post-launch, deliver on the goal of driving lower healthcare costs and increased savings. Biosimilar competition breaks the price increase trends with reference agents and contributes to a decrease in reference agent drug reimbursement. The effects of manufacturer rebates, payer policies, 340b programs, and discounts on ASP and Medicare reimbursement are also areas of active investigation.
Retrospective analysis: Does 5-FU dose adjustment per DPYD mutation status affect toxicity?
Authors: Deevyashali Parekh, Vanita Noronha, Vijay Maruti Patil, Nandini Sharrel Menon, Minit Jalan Shah, Anuradha Chougule, Kumar Prabhash
Journal: Journal of Clinical Oncology (2024)

11172 Background: 5-Fluorouracil (5-FU) forms a cornerstone in neoadjuvant chemotherapy (NACT) regimens for solid tumors including head and neck cancers. The DPYD gene encodes for enzyme dihydropyrimidine dehydrogenase (DPD) which catalyses an essential, rate-limiting step in the metabolism of 5-FU. Heterozygous genomic alteration of DPYD (30-35% of population) result in reduced potency of DPD enzyme, while homozygous DPYD alteration (0.1-0.2% of population) results in no functional DPD. Reduced functioning of DPD leads to slower metabolism of 5-FU causing toxicity such as bone marrow suppression, cytopenias etc. The Clinical Pharmacogenetics Implementation Consortium (CPIC) have released guidelines recommending reducing the dose of 5-FU in patients with these genomic alterations of DPYD from 25% to avoiding its use based on a calculated activity score (DPYD-AS). Methods: A phase III randomized study compared a DC vs DCF regimen as NACT in technically unresectable oral cancer was published in March 2024. We utilised data from the ‘DCF’ arm of this study. Patients underwent DPYD testing and we stratified these patients based on DPYD status. In the study, patients underwent the appropriate dose reductions per the CPIC guidelines based on DPYD-AS scores. We evaluate the frequency and degree of adverse events in these groups to determine whether this dose reduction effectively reduces toxicity from 5-FU in these patients. Adverse events were graded per CTCAE. Analysis by Fishers exact test. Results: 247 patients in the DCF arm were included. 85 (34.4%) did not undergo DPYD testing. 118 (47.8%) did not have any DPYD mutation, 44 (17.8%) had heterozygous mutation while 0 had homozygous mutation. The adverse events by DPYD genotypic subgroup are shown in the table. Conclusions: There was no statistically significant difference in adverse events between the group with no DPYD mutation who received the full dose of 5-FU and the heterozygous DPYD mutation group receiving a lower 5-FU dose based on DPYD-AS score. Thus, the dose reduction as set out by the CPIC appears to appropriate. [Table: see text]
Incorporating precision oncology in everyday clinical practice: First two years of comprehensive genomic profiling (CGP) testing experience in Croatia.
Authors: Dora Čerina, Jelena Šuto Pavičić, Antonela Njavro, Niksa Librenjak, Ilijan Tomaš, Robert Šeparović, Stjepko Plestina, Žarko Bajić, Natalija Dedic Plavetic, Eduard Vrdoljak
Journal: Journal of Clinical Oncology (2024)

11151 Background: Despite increased availability of modern technologies and evolution of tailored treatment, which has already significantly changed the outcomes in some cancer types, applicability of precision medicine in everyday clinical practice is still emerging and is one of the hot topics. Croatia is among first ones in the World to have entered into force a country-level based project of precision oncology throughout the CGP analysis in everyday clinical work, fully covered by Croatian health insurance. Hence, here we would like to present our data from everyday clinical practice and analyze the penetration of CGP given the opportunity and challenges we had. Methods: The study was observational and retrospective in nature, conducted on a country level among all patients on whose tumor specimens CGP was performed between January 1, 2020 and December 31, 2021. Eligible patients for the CGP analysis were those with metastatic disease, with at least 6-12 months of life-expectancy, with ECOG performance status ≤ 2, and after the recommendation from the multidisciplinary team. The analysis was performed in accredited laboratory (Foundation Medicine Inc., Cambridge, MA, USA), through FoundationOneCDx for solid tumors, FoundationOne Liquid in case of insufficient tissue or FoundationOneHeme for sarcomas. Results: There was total of 481 patients with CGP results. Median age was 61 years (IQR 49-69) and 58% of patients were women, while 42% were men. Most commonly tested were gastrointestinal (29.1%) and reproductive tumors (28.9%) with colorectal (19.1%) and uterine cancer (11.2%) as the most prevalent. At least one clinically relevant genomic alteration was found in 48.7% of patients. The most frequent mutations were those of KRAS (27.2%), PIK3CA (12.9%), AR (10.6%), NRAS (10.4%) and PTEN (9.1%) genes. Currently clinically not relevant mutations were found in 51.8% of patients with TP53 gene mutation as the most common (42.8%). According to the Croatian cancer registry, there was around 26 000 cancer related deaths during the investigated period defining population of at least more than 10 000 potentially eligible patients for the CGP analysis. Conclusions: Our results have shown that almost 50% of tested patients could have potential treatment benefit based on the detection of clinically relevant genomic alteration. Unfortunately, taking into consideration country level insurance eligibility criteria for CGP testing and number of potentially eligible cancer patients, we could say that only less than 5% of patients with metastatic disease were tested within first two years and that penetration of CGP is rather low, resulting with a significant number of patients underserved.
Census tract–level social determinants of health and variability in stage at diagnosis of bladder, breast, and non-small cell lung cancers.
Authors: henry G Kaplan, Molly Scannell Bryan, Xiaohan Hu, Hina Mohammed, Monika A. Izano, Thomas D. Brown, George R. Simon, Jose A. Karam, Anna B. Berry
Journal: Journal of Clinical Oncology (2024)

11170 Background: Social determinants of health (SDOH) can identify underserved populations, inform the patient journey, and identify opportunities to improve outcomes. In cancer, SDOH may influence stage at diagnosis through exposure to risk factors for aggressive cancer and decreased access to care. However, privacy restrictions can limit research with SDOH in real world datasets, which often only know a patient’s broad location. Methods: Geocoding was undertaken on addresses of patients diagnosed between 1/1/17 and 9/30/22 with bladder (n=6078), breast (n=28,958), and non-small cell lung cancer (NSCLC, n=14,957) in the Syapse Learning Health Network of U.S. community health systems. Location was linked to five indicators of SDOH at the census tract level: the Social Vulnerability Index (SVI); percent (%) of tract spending &gt;30% of income on housing; % of tract with broadband internet; county designation as a primary care shortage area; and rural urban commuting area (RUCA). Nested multivariable ordinal logistic regression models estimated independent associations between demographic, clinical, and SDOH factors with stage at initial cancer diagnosis. The statistical significance of including SDOH variables was assessed using a likelihood ratio test (LRT) comparing the models before and after including SDOH. Results: After successful geocoding and linkage to census tracts, there were marginal differences in the distribution of the five SDOH across stages at diagnosis within the three tumor types. In multivariable models adjusted for year of diagnosis, age, sex, race, ethnicity, smoking, and primary payor, among the tested SDOH measures, county designated as primary care shortage (proportional odds ratios (OR): 1.31, 95% confidence interval (95% CI): 1.05-1.64), and non-metropolitan area (0.69, 0.50-0.94) were statistically significantly associated with stage at bladder cancer diagnosis. SVI (1.52, 1.31-1.76) was also statistically significantly associated and directly proportional with stage at breast cancer diagnosis. Among patients with NSCLC, broadband internet access (1.01, 1.00-1.01), primary care shortage (1.15, 1.03-1.27) and non-metropolitan area (0.85, 0.74-0.99) were statistically associated with stage at diagnosis. In all three tumors, LRTs found that models with SDOH were statistically significantly better at predicting stage at diagnosis than those without (p &lt;0.001). Conclusions: Using granular, census-tract geospatial resolution for geocoding of SDOH, we find that patients who live in greater vulnerability are diagnosed at later stages than those who live in areas of less vulnerability, suggesting that consideration of SDOH variables is important in assessing stage at diagnosis and identify patients with an unmet need for outreach and screening.
Racial and socioeconomic disparities in survival among patients with metastatic non–small cell lung cancer
Authors: Dipesh Uprety, Randell Seaton, Tarik Hadid, Hirva Mamdani, Ammar Sukari, Julie J Ruterbusch, Ann G Schwartz
Journal: JNCI Journal of the National Cancer Institute (2024)

Abstract Background Immune checkpoint inhibitors have profoundly impacted survival among patients with metastatic non–small cell lung cancer. However, population-based studies evaluating this impact on survival by race and socioeconomic factors are lacking. Methods We used the Surveillance, Epidemiology, and End Results Program–Medicare database to identify patients with metastatic non–small cell lung cancer diagnosed between 2015 and 2019. The primary study outcomes were the receipt of an immune checkpoint inhibitor and overall survival. χ2 tests and logistic regression were used to identify demographic factors associated with receipt of immune checkpoint inhibitors. The Kaplan–Meier method was used to calculate 2-year overall survival rates, and log-rank tests were used to compare survival by race and ethnicity. Results Of 17 134 patients, approximately 39% received an immune checkpoint inhibitor. Those diagnosed with cancer recently (in 2019); who are relatively younger (aged younger than 85 years); non-Hispanic White, non-Hispanic Asian, or Hispanic; living in high socioeconomic status or metropolitan areas; not Medicaid eligible; and with adenocarcinoma histology were more likely to receive immune checkpoint inhibitors. The 2-year overall survival rate from diagnosis was 21% for the overall population. The 2-year overall survival rate from immune checkpoint inhibitor initiation was 30%, among those who received at least 1 cycle and 11% among those who did not receive immune checkpoint inhibitors. The 2-year overall survival rates were higher among non-Hispanic White (22%) and non-Hispanic Asian (23%) patients compared with non-Hispanic Black (15%) and Hispanic (17%) patients. There was no statistically significant racial differences in survival for those who received immune checkpoint inhibitors. Conclusion Immune checkpoint inhibitor utilization rates and the resulting outcomes were inferior for certain vulnerable groups, mandating the need for strategies to improve access to care.