tbuckley/cabot-search huggingface dataset:
Predictive and pharmacodynamic biomarkers for combination therapy in stage III-IV melanoma: A Simon phase II trial (NCT03999749).
Authors: Teruyuki Mizutani, Tomoaki Muramatsu, Joanna Handzlik, Diana Kimono, Ankita Mitra, Eddy Yang, Tomas Kirchhoff, Amrutesh Puranik, Jeffrey S. Weber
Journal: Journal of Clinical Oncology (2024)

222 Background: The evaluation of biomarkers that predict response and immune-related adverse events (irAEs) is crucial for optimizing melanoma treatment with Immune checkpoint inhibitors (ICIs). We report predictive and pharmacodynamic biomarkers for response and irAEs using high-dimensional flow cytometry in a phase II trial combining nivolumab (3 mg/kg), ipilimumab (1 mg/ml), and the IL-6 receptor inhibitor tocilizumab (4 mg/kg) in unresectable/advanced melanoma patients. Methods: We analyzed serum and blood from melanoma patients at baseline, weeks 7 and 37, categorized them by irAE severity and clinical response. Patients were categorized based on the severity of irAEs (grades 3-5) (TOX), the absence of toxicity or grades 1-2 irAE (NT), clinical benefit (CB), and non-clinical benefit (NCB). Immune monitoring regimen included ELISA for IL-6, gp130, IL-23, osteopontin, and Luminex oncological panel (LXSAHM-22). We employed multi-parametric flow cytometry panels to examine myeloid cells, cytotoxic T cells, and checkpoint protein expression on immune cells. We processed ~1 million PBMCs per sample using various antibodies, with data acquisition performed via Sony’s ID7000 cytometer. The data underwent quality control, normalization PBMCs per patient, concatenation, dimensionality reduction, and clustering in FlowJo. Results: Among the 70 patients administered treatment, we observed a best overall response rate of 57%. Grade 3-5 irAEs occurred in 22% of patients by week 24. Patients manifesting irAEs exhibited notably higher baseline Th17 cell counts (NT=181±18 vs. Tox=311±49, p&lt;0.01) and CD26+ Naive CD4 T-cell populations (NT=5838±801 vs. Tox=9632±1343, p&lt;0.04), suggesting their potential role as predictive markers for toxicity. Additionally, in vitro investigations led us to identify CD26 co-stimulation as a preliminary step in TH17 cell differentiation. Key pharmacodynamic markers included a significant elevation in Treg cells (NCB=1286±71 vs. CB=1492±95, p=0.02) and reduction in serum gp130 levels (NCB=104±5 vs. CB=83±5 ng/ml, p&lt;0.01) at week 7 in addition to IL-6 (NCB=7.5±1.5 vs. CB=4.6±1.1 pg/ml, p&lt;0.01) and osteopontin (NCB=95±15 vs. CB=25±3 ng/ml, p&lt;0.01) by week 37 when compared to baseline. Conclusions: Our findings suggest that Th17 cells can serve as a toxicity biomarker for combination therapy with ipilimumab, nivolumab and tocilizumab. Circulating Treg cells and serum osteopontin have emerged as promising pharmacodynamic biomarkers. Clinical trial information: NCT03999749 .
Comparative analysis of cirrhosis and hepatocellular carcinoma outcomes in Asian populations with non-alcoholic fatty liver disease (NAFLD) and metabolic dysfunction-associated steatohepatitis liver disease (MASLD): A five-year retrospective study.
Authors: Yuan-Tsung Tseng, Chun-Hsiang Wang
Journal: Journal of Clinical Oncology (2024)

78 Background: Metabolic Dysfunction-Associated Steatohepatitis Liver Disease (MASLD) represents the most up-to-date definition of Non-Alcoholic Fatty Liver Disease (NAFLD) for Asian populations, acknowledging that manifestations may differ across racial/ethnic groups. Due to metabolic and anthropometric differences, adapted criteria for MASLD have been proposed for Asian adults. This analysis aims to compare clinical outcomes between Asian patients diagnosed with MASLD and those with NAFLD. Methods: In this retrospective analysis, 48,189 Asian adults suspected of having MASLD were identified from the TriNetX global research network between January 1, 2010 and December 31, 2023. An equal number of patients (48,189) diagnosed with NAFLD were matched on a 1:1 basis with MASLD patients through propensity score matching. MASLD criteria were adapted to be Asia-specific, requiring a Body Mass Index (BMI) of ≥23 along with the presence of four aspects of metabolic dysfunction. Over a 5-year follow-up period, primary outcomes of cirrhosis and hepatocellular carcinoma (HCC) incidences were determined using Kaplan-Meier methods. Cumulative incidence curves depicted the rates of these events over time. Hazard ratios (HR) for the outcomes were calculated using Cox regression models to estimate the risk associated with MASLD. Results: Over 5 years, the cumulative incidence of cirrhosis (3.0% vs 3.0%, p=0.800) and HCC (1.3% vs 1.4%, p=0.695) were numerically lower in MASLD compared to NAFLD patients, respectively. Adjusted HRs for MASLD were: cirrhosis 1.00 (0.87-1.14) and HCC 0.86 (0.68-1.10). Conclusions: This study compared the clinical outcomes of MASLD and NAFLD in Asian populations and found no significant differences in identifying the risk of cirrhosis and hepatocellular carcinoma between the two diagnostic criteria. However, introducing the new term and diagnostic criteria of MASLD helps reduce the stigmatization associated with NAFLD, emphasizing the central role of metabolic dysfunction in disease occurrence. Although this study did not find significant differences between MASLD and NAFLD in predicting cirrhosis and hepatocellular carcinoma, the concept of Asian-specific diagnostic criteria remains important, highlighting that disease manifestations and risk factors may vary across different races and populations, necessitating personalized prevention and treatment strategies for specific populations. Future research should further explore the similarities and differences between MASLD and NAFLD in different Asian subgroups to optimize diagnostic criteria, improve the accuracy of risk prediction, and develop targeted interventions.
Effect of impaired autophagic flux on breast carcinogenesis through the enhanced LC3-p62-NRF2 feedback loop.
Authors: Mehreen Aftab, Kamran Waidha, Jacob Gopas, Showket Hussain
Journal: Journal of Clinical Oncology (2024)

6 Background: Breast cancer affects more women worldwide than any other type of cancer. Although some genes have been identified as potential causes, the exact molecular mechanism of the disease is still unknown. In our study, we aimed to investigate the role of NRF2 and the autophagy markers p62 and LC3 in breast cancer cell lines that have different Tp53 status using a new compound called 6,6'dihydroxythiobinupharidine (DTBN). In our previous research, we have shown that DTBN modulates key cellular signal transduction pathways that are relevant to disease biology, including cancer. Furthermore, we analyzed online databases to determine the correlation between NRF2, p62, LC3, and Tp53 in breast cancer patients. Methods: To evaluate the effect of DTBN on NRF2, p62 and LC3 in different types of breast cancer cell lines with varying TP53 status, we conducted molecular studies by inhibiting NRF2 activity. We synthesized the correlation between NRF2, p62, LC3 and TP53 expression and clinical parameters by analyzing TCGA and GEO datasets. Results: Our findings suggest that DTBN induces cell death and autophagy in all breast cancer cell lines, regardless of their Tp53 status. However, they also led us to hypothesize that NRF2 may hinder the sensitivity of cancer cells to DTBN-induced cell death and autophagy. To test this hypothesis, we inhibited NRF2 activity using an NRF2 inhibitor called brusatol. The results of the study indicate that the inhibition of NRF2 significantly increased cell death and autophagy in DTBN-treated cells. We observed a decrease in the expression of the autophagy marker p62, while an increase in the expression of another autophagy marker LC3. These findings suggest that the interaction between NRF2, LC3 and p62, which is activated in response to DTBN treatment, may serve as a potential anticancer drug target. We have validated the positive correlation between NRF2 and the autophagic gene p62 and LC3, in different Tp53 status breast cancer cell lines by analyzing TCGA and GEO data. Conclusions: Our study shows that high levels of Nrf2, LC3 and p62 expression are significantly associated with increased breast cancer cell proliferation and migration. This implies that patients with breast cancer have lower overall survival and a higher rate of recurrence. Our findings highlight the role of DTBN-induced NRF2 and LC3 expression and reduced p62 expression in breast cancer cells with varying Tp53 status. These results may represent a paradigm for better understanding the cancer cell response to therapies and designing more efficient combined anticancer therapies targeting NRF2, LC3 p62, and Tp53.
The pathogenic role of retinoid nuclear receptor signaling in cancer and metabolic syndromes
Authors: Mark Esposito, John K. Amory, Yibin Kang
Journal: The Journal of Experimental Medicine (2024)

The retinoid nuclear receptor pathway, activated by the vitamin A metabolite retinoic acid, has been extensively investigated for over a century. This study has resulted in conflicting hypotheses about how the pathway regulates health and how it should be pharmaceutically manipulated. These disagreements arise from a fundamental contradiction: retinoid agonists offer clear benefits to select patients with rare bone growth disorders, acute promyelocytic leukemia, and some dermatologic diseases, yet therapeutic retinoid pathway activation frequently causes more harm than good, both through acute metabolic dysregulation and a delayed cancer-promoting effect. In this review, we discuss controlled clinical, mechanistic, and genetic data to suggest several disease settings where inhibition of the retinoid pathway may be a compelling therapeutic strategy, such as solid cancers or metabolic syndromes, and also caution against continued testing of retinoid agonists in cancer patients. Considerable evidence suggests a central role for retinoid regulation of immunity and metabolism, with therapeutic opportunities to antagonize retinoid signaling proposed in cancer, diabetes, and obesity.
Delayed addition of PD-1/PD-L1 inhibitors into chemotherapy on the outcomes for patients with extensive-stage small cell lung cancer: A propensity score-matched study.
Authors: Shuangqing Lu, Yaru Tian, Hui Zhu
Journal: Journal of Clinical Oncology (2024)

208 Background: Immunotherapy in combination with chemotherapy has become the first-line treatment for extensive-stage small cell lung cancer (ES-SCLC). However, some patients failed to undergo simultaneous immunotherapy at the time of initial chemotherapy, and whether this will have an impact on the efficacy of immunochemotherapy has not been fully explored. Methods: Between January 2020 and December 2022, the study included 416 patients diagnosed with ES-SCLC and receiving first-line immunotherapy, divided into two groups: delayed-IO (administering PD-1/PD-L1 inhibitors at 2-4 Cycles of chemotherapy) and early-IO (administering PD-1/PD-L1 inhibitors concurrent with first-cycle chemotherapy). Propensity score matching (PSM, 1:1) was performed to balance the baseline characteristics of the two groups. The primary endpoints were OS and PFS. Calculations were performed using the Kaplan-Meier method and comparisons were made using the log-rank test. Results: Mainly due to the fact that PD-L1/PD-1 inhibitors were not included in the medical insurance, which was difficult for patients to afford and the poor physical condition of some patients, taking into account the safety of the patients themselves, 72 patients in the delayed-IO group (2 cycles of chemotherapy: 41; 3 cycles: 16; 4 cycles: 15), and 344patients were included in the early-IO group. The median OS and PFS were 24.00 months and 8.75 months in the delayed-IO group, and those were 18.59 months and 7.57 months in the early-IO group, respectively, before PSM. There was no significant difference in OS and PFS between the two groups (HR 0.72; P = 0.054 and HR 0.86; P = 0.281, respectively). After PSM, there were 72 patients in each of the two groups. The median OS in the delayed-IO group and the early-IO group was 24.00 months and 18.79 months, respectively (HR 0.60, 95% CI 0.38-0.97; P = 0.037). Median PFS was 8.75 and 6.49 months in the two groups, respectively (HR 0.69, 95% CI 0.48-0.99; P = 0.044). There was a statistically significant difference between the two groups. The overall adverse event profile was comparable between the two groups. Conclusions: Our findings suggest that administering PD-1/PD-L1 inhibitors at 2-4 Cycles of chemotherapy was superior to administering PD-1/PD-L1 inhibitors concurrent with first-cycle chemotherapy in patients with ES-SCLC, while the safety profile of both was similar.
Hospitalization outcome of patients with lung cancer with COVID-19 infection: NIS 2020 analysis.
Authors: Thanathip Suenghataiphorn, Thitiphan Srikulmontri, Narathorn Kulthamrongsri, Narisara Tribuddharat, Piengpitch Naunsilp, Sakditad Saowapa, Nutchapon Xanthavanij
Journal: Journal of Clinical Oncology (2024)

212 Background: Lung cancer is the most commonly diagnosed cancer and the leading cause of cancer-related deaths globally. Recent data showed the detrimental effects of COVID-19 infection on other neoplasm conditions, causing increased mortality rates and complications. However, data on the precise effects of COVID-19 on hospitalized individuals with lung cancer are scarce. Methods: We analyzed the 2020 U.S. National Inpatient Sample (NIS) to investigate the effects of COVID-19 infection on cases primarily admitted due to lung and bronchus cancer. Adjusted odds ratios (aORs) for specified outcomes were calculated through multivariable logistic and linear regression analyses. The primary outcome was inpatient mortality, with secondary outcomes including system-based complications. Statistical significance was established at a p-value of 0.05. Results: We identified 103,334 patients with a primary discharge diagnosis of lung and bronchus cancer. The mean age was 68.9 years; 50.5% were female. In the non-COVID group, Caucasians accounted for 75%, followed by Hispanics (12%). Of these, 0.36% (374/103,334) had a concurrent diagnosis of COVID-19 infection. In a survey multivariable logistic and linear regression model adjusting for patient and hospital factors, COVID-19 infection was associated with higher in-hospital mortality (aOR 5.39; 95% CI (3.01, 9.64), p &lt; 0.001), higher mean length of stay (b 5.51; 95% CI (2.59, 8.43) p &lt; 0.001), mean total hospital cost (b 10,683; 95% CI (784.32, 20,581.93) p = 0.034), shock (aOR 4.37; 95% CI (1.96, 9.91), p &lt; 0.001), acute respiratory failure (aOR 2.23; 95% CI (1.30, 3.85), p = 0.004), mechanical ventilation usage (aOR 3.12; 95% CI (1.46, 6.66), p = 0.003) and acute kidney injury (aOR 2.71; 95% CI (1.54, 4.74), p &lt; 0.001). We observed non-significant, but increased, risks of sepsis, SIRS, and coagulopathy in COVID-19-positive patients. Conclusions: In conclusion, our study underscores that COVID-19 infection is associated with higher in-hospital mortality and other major clinical outcomes in lung cancer, as well as increased economic burden and cost of stay. To definitively establish causal relationships between the observed factors and the reported clinical outcomes in this population, further longitudinal research is necessary.
Utilizing an automated cloud-based platform, Palantine Foundry, to generate and build large databases for clinical research applications.
Authors: Quynh Nguyen, Julius Weng, Paul Edelkamp, Mark Knafl, Paul Roy, David C Qian, Zhongxing X. Liao, Scott Eric Woodman
Journal: Journal of Clinical Oncology (2024)

165 Background: Academic institutions are adopting automated tools to help develop and maintain large databases. Leveraging advances in clinical data warehouses and artificial intelligence can potentially decrease resource utilization and the time required to conduct research by reducing intensive manual human curation of data. Methods: This research was performed as part of the institutional Data-Driven Determinants for COVID-19 Oncology Discovery Effort (D3CODE), IRB-approved protocol 2020-0348. Data were obtained from both structured and unstructured data sources within the MD Anderson electronic health record to validate a retrospective analysis for COVID-19 positive patients undergoing radiation treatments. Multiple data sources were identified, integrated and analyzed using the Syntropy Foundry platform, part of the Context Engine Data Management System at M.D. Anderson Cancer Center (MDACC) to include patient demographics, clinical notes, laboratory values, radiology reports, and oncology treatments. The platform allows real-time updating of these data-sources with integrated statistical packages to streamline rapid statistical analyses. We conducted a retrospective review of patients treated within 3 weeks of COVID infection between March 2020 and November 2022. Patient data was obtained using Foundry. Patients who tested positive for COVID-19 and had their treatment postponed were categorized as having a treatment delay. Patients who started radiation therapy and subsequently had an interruption in treatment due to contracting COVID-19 were categorized as having a treatment break. The Kaplan-Meier method was used to compare survival outcomes and was conducted within Foundry. Results: Syntropy Foundry helped develop a database comprising of 380 COVID-19 positive patients treated with radiation therapy between March 2020 through November 2022. It validated patient demographic information and research variables including patient age, histology, cancer stage, treatment plans, radiographic scans, recurrences, and follow up time that were separately performed manually. It reduced the time and human resources required to retrospectively collect and review these patient charts. Conclusions: Syntropy Foundry and ongoing efforts to leverage machine learning models to facilitate the interpretation of the large amount of accessible clinical data can potentially improve quality and reduce resources needed to generate large research databases. Future applications using artificial intelligence with Foundry to identify clinical recurrence and report patient outcome are under development.
Perioperative FLOT + immunotherapy for resectable gastric and gastroesophageal junction cancer: A systematic review and meta-analysis.
Authors: Lorenz Fort Estrada Revillas, John Kelvin Lalusis, Carlos Dy
Journal: Journal of Clinical Oncology (2024)

66 Background: The current standard of care for resectable gastric and GEJ cancers is perioperative chemotherapy with FLOT.Although its benefits in improving rates of pathologic complete response, increasing prospects of R0 resection, and improving survival have been proven, efforts to find novel strategies which can improve on its gains continue.The addition of an immune checkpoint inhibitor to FLOT has been a focal point of research in this field. This meta-analysis evaluated high-quality data from clinical trials to determine the efficacy of this chemoimmunotherapy combination. Methods: A systematic search of English-language articles on PubMed, Cochrane and Google scholar was done to identify randomized trials investigating the use of perioperative FLOT and immune checkpoint inhibitors in the treatment of resectable gastric and GEJ cancer. Quality of studies was assessed using the Revised Cochrane risk-of-bias tool for randomized trials. Inverse variance was the statistical method used with random effects as the analysis model in the production of the Forest plot and calculation of odds ratio at 95% CI. Results: Three RCTs (N = 1446), each with two arms, were included in the meta-analysis. The Phase II Dante Trial (N= 295)compared perioperative FLOT alone with perioperative atezolizumab + FLOT. The Phase III Keynote 585 trial(N=203) and the phase III Matterhorn trial (N=948) compared perioperative placebo + FLOT with perioperative pembrolizumab + FLOT, and perioperative Durvalumab + FLOT, respectively. Risk of bias and heterogeneity were low. Pooled results showed that in patients given perioperative FLOT + immunotherapy, there is statistically significant improvement in the rate of pathologic complete response (OR 2.60 95% CI 1.88-3.61, p &lt;0.0001). In terms of rate of R0 resection, there was no statistically significant difference between the two groups (OR 1.02 95% CI 0.75-1.38,p= 0.92). Conclusions: This analysis shows that adding immunotherapy to FLOT improves the rate of pathologic complete response, and maintains the high rate of R0 resection, in resectable gastric and GEJ cancers. Favorable results of pending survival outcomes from these trials may help re-shape the current standard of care in this field.
Utility of radiomic features in predicting clinical outcomes in stage II-III pancreatic cancer.
Authors: Haruka Itakura, Qinmei Xu, Diego Toesca, Lucas Vitzthum, Arash Jamalian, Emil Schueler, Emel Alkim, J Richelcyn Baclay, Daniel Tandel Chang, George A. Fisher
Journal: Journal of Clinical Oncology (2024)

74 Background: We identified computed tomography (CT)-derived radiomic features predictive of tumor progression within three months, then examined their ability to prognosticate overall survival (OS) along with clinical features in pancreatic cancer. We evaluated these features in patients with unresected pancreatic cancer who underwent stereotactic body radiation therapy (SBRT) in sequence with chemotherapy, but not surgery. Methods: In this retrospective study, we examined a cohort of 101 patients with stage II-III pancreatic cancer who underwent SBRT with sequential chemotherapy at a single institution (Stanford Health Care) between 1999-2020. From their pre-SBRT contrast-enhanced CT images with segmented tumors, delineating regions-of-interest, we extracted 900 radiomic (quantitative pixel-level imaging characteristic) features. In the first phase, we identified radiomic features that predicted rapid tumor progression within three months following SBRT. We divided the dataset into a training set (n = 53) for model development and a test set (n = 48) for evaluation. Using logistic regression with the Least Absolute Shrinkage and Selection Operator algorithm for feature selection and classification, we built a binary prediction model on the training set to identify patients at risk of progression within three months of SBRT. To fine-tune parameters, we performed five-fold cross-validation (CV) on the training set, repeating each set of parameters five times. We assessed model performance on the test set using the area under the curve (AUC). We selected the model with the best AUC, generating the predictive radiomic feature set. In the second phase, we conducted univariate and multivariate Cox regression analyses to assess the relationship between OS and individual clinical variables (age, sex, stage, vessel involvement, tumor location, performance status, body mass index, biological equivalent dose of radiation) and the radiomic feature set as high versus low risk. Results: Our cohort consisted of 48 men (mean age, 70 years ± 11 [SD]) and 53 women (mean age, 67 years ± 13 [SD]). From the first phase, 32 textural features comprised the radiomic feature set that best predicted rapid tumor progression, with mean AUCs of 0.852 (CV, n=53) and 0.814 (test, n=48). In the univariate Cox model, only the radiomic feature set was predictive of OS (hazard ratio, HR, 1.724, p=0.011). In the multivariate Cox model, radiomic features and age were significant predictors of OS, with HR of 1.819 (p=0.007) and 1.024 (p=0.024), respectively. Conclusions: CT-derived radiomic features predict rapid tumor progression following SBRT, confer nearly a twofold increase in mortality risk, and, along with patient age, enhance the identification of patients with stage II-III pancreatic cancer with poor OS. [Table: see text]