bluuebunny/crossref_metadata_2025 huggingface dataset:
A novel three-biomarker signature (CA-62, CEA, CYFRA 21-1) and early-stage NSC lung cancer detection.
Authors: Tcherkassova Janneta , Tsurkan Sergei , Prostyakova Anna , Klinski Evgueni , Sekacheva Marina , Boroda Alexander , Moro Ricardo , Berz David
Published: June 2023

3038

Background: A double-blind clinical study was conducted on 304 clinically verified blood serum samples, including 141 non-small cell lung cancer (NSCLC), 133 healthy volunteers and 30 patients with chronic obstructive pulmonary disease (COPD). The objectives of the study were: The assessment of various cancer markers and their possible combinations for detection of early (I-II) stages of non-small cell lung cancer (NSCLC) and evaluation of the best cancer markers panel as a pre-screening tool for NSCLC before Low-Dose CT scan. Methods: Quantitative measurement of various tumor markers for serum samples was carried out using electrochemiluminescent immunoassays Elecsys CA-125, ELECSYS CA 19-9, ELECSYS CYFRA 21-1 and ELECSYS SCC (COBAS, Roche Diagnostics GmbH, Germany, EU), enzyme immunoassay CA15-3-ELISA-BEST, CEA-ELISA-BEST, NSE-ELISA-BEST (JSC "VECTOR-BEST", RF) and immunochemiluminescent analysis CLIA-CA-62 (LLC "JVS Diagnostics", RF). The results were compared to the literature data for other biomarkers and their panels. Results: Unlike other tumor markers, which are expressed proportionally to tumor size, the marker for epithelial carcinomas CA-62 is expressed from Stage I and demonstrated the highest diagnostic results in detecting early stages (I-II) of NSCLC. The biomarkers CYFRA 21-1 and SCC do not have sufficient sensitivity and specificity to diagnose asymptomatic lung cancer. However, the addition of cytokeratin 19 CYFRA 21-1 to glycoproteins CA-62 and CEA increases the specificity by eliminating false positive results, which significantly improves the diagnostic value of the cancer marker signature (CA-62, CEA and CYFRA 21-1): 100% Specificity, 93% Sensitivity, 100% PPV, 94% NPV and 94% test accuracy. Conclusions: The results of the study demonstrated that using the biomarkers signature (CA-62, CEA and CYFRA 21-1) allows increasing the specificity of CT scan for patients with suspicious abnormalities on the tomogram, improving the interpretation of visualized localized lesion, and improving the accuracy of differential diagnosis at detecting early stages of LC up to 94%. In the prospective, adding cancer markers panel signature (CA-62, CEA and CYFRA 21-1) to the current lung cancer risk assessment system as a pre-screening tool for LDCT may improve the quality of early-stage Lung cancer detection by significant increasing the sensitivity and by reducing the proportion of false positive results. [Table: see text]
The detection of multiple cancer types with an extended set of methylation and protein markers.
Authors: Katerov Slava E. , Fleming Harrison L , Rugowski Debra E , Heilberger Justin , Duellman Tyler , Kirby Jillian M , Kirchner Nick , Melah Brittany , Hennek Jacquelyn , Allawi Hatim T.
Published: June 2023

3040

Background: Cancer is the 2nd leading cause of mortality in the US, with an estimated 1.96M new cases expected in 2023. With guideline recommended screening unavailable for most cancers, multicancer early detection (MCED) tests in development may extend the reach of cancer screening. As part of an ongoing program examining multiple biomarker classes in cancer early detection, we examined the feasibility of combining blood DNA methylation and cancer protein markers for the detection of multiple cancer types. Methods: 236 samples from subjects with cancer (13 tumor organ types) were retrospectively collected and gender/age matched with 146 unscreened non-cancer control samples. Plasma and serum were used for cfDNA methylation analysis of 36 differentially methylated regions and 8 cancer-associated protein markers in a randomized, blinded fashion. Methylated DNA markers (MDMs) were assayed using target enrichment long-probe quantitative-amplified signal assays. Protein markers were assayed with commercial kits. Normalized methylation values/protein concentrations were used to develop a logistic regression model for cancer detection. The model was built with 5 random 0.7/0.3 training/validation splits, keeping case/control, cancer types, gender, and age distributions similar to the original data set. Models for MDMs and protein markers were created, and a combined model including both MDMs and protein markers was also evaluated for performance improvement. Results: A reduced subset of MDM and protein markers was identified to have robust detection of several cancer types. At 99% specificity, overall sensitivity for cancer detection was 68% (95% CI: 62%-74%) for MDMs, 43% (37%-50%) for proteins, and 75% (69%-80%) for MDMs and proteins combined. Conclusions: Building on promising results with mutation and protein biomarker analysis (Science 369:6499, 2020) this pilot study demonstrates the potential of combining DNA methylation and protein biomarkers and contributes to a larger scale effort to develop a multi-biomarker class MCED test (Ann Oncol 2022 Vol. 33:S575). [Table: see text]
ctDNA-based genomic landscape analysis to evaluate molecular brake and gatekeeper mutations in FGFR2 alterations.
Authors: Severson Paul , Sytnikova Julia , Mohan Adithi , Zhang Nicole , Donderici Elifnur Yay , Williams Richard Thomas
Published: June 2023

3049

Background: FGFR2 and FGFR3 (FGFR2/3) gene alterations are oncogenic drivers found across various cancer types and have been successful targets of drug development. Several FGFR inhibitors (FGFRi) are approved for clinical use, and most are ATP-competitive, reversible inhibitors (1st-gen). Efficacy of the 1st-gen FGFRi can be limited by acquired resistance mutations in the FGFR kinase domain, typically molecular brake or gatekeeper mutations, which disrupt compounds binding through conformational changes or through direct steric hindrance, respectively. Irreversible (covalent) FGFRi, such as futibatinib, are in development to overcome kinase domain resistance mutations. However, preclinical evidence indicates that some of the known resistance mutations (eg. V564L) remain insensitive to futibatinib. Methods: To assess the landscape of FGFR-driven cancers and to better understand the prevalence of molecular brake and gatekeeper mutations, we analyzed the distribution of FGFR2/3 alterations in a large clinical genomic research database. This ctDNA-based genomic database was selected for the analysis given that liquid biopsy is a fit-for-purpose method to detect acquired resistance mutations. Results: We identified over 2,100 patients with FGFR2/3 alterations. Non-small cell lung cancer (NSCLC), breast, bladder, and cholangiocarcinoma (CCA) had the highest number of patients with FGFR2/3 alterations. 36% of all FGFR2 alterations across all cancer indications consisted of molecular brake or gatekeeper mutations. This finding was most enriched in CCA and breast cancer where 51% and 57%, respectively, of FGFR2 alterations were molecular brake or gatekeeper mutations. In breast cancer patients, molecular brake mutations were common and represent activating mutations in FGFRi-naïve patients. A small number of FGFR3 gene fusions were detected in CCA patients who had significantly shorter time on 1st-line treatment and trended toward shorter overall survival when compared to patients with FGFR2 fusions. We also identified CCA patients with FGFR2 fusions and one or more concurrent FGFR2 SNVs; primarily those in the kinase domain and associated with FGFRi resistance. Most of these putative cases of acquired resistance were polyclonal, with 2 or more (up to 8) FGFR2 SNVs coexisting with the fusion. Bladder cancer and NSCLC had the highest numbers of FGFR3 alterations. FGFR2/3 alterations were typically found without other driver mutations in CCA, bladder, and NSCLC patients. However, in breast there was a large overlap between FGFR2/3 alterations and other drivers. Conclusions: Herein, we identify a cohort of patients with FGFR2/3 molecular brake and gatekeeper mutations that may benefit from next-generation FGFR2/3-targeted therapies designed to inhibit a broad spectrum of both primary and secondary resistance mutations.
Detection of early-stage cancers using circulating orphan non-coding RNAs in blood.
Authors: Karimzadeh Mehran , Wang Jeffrey , Cavazos Taylor B. , Schwartzberg Lee S. , Multhaup Michael , Ku Jeremy , Zhao Xuan , Wang Jieyang , Wang Kathleen , Hanna Rose , Arensdorf Patrick , Chau Kimberly H , Li Helen , Goodarzi Hani , Fish Lisa , Hormozdiari Fereydoun , Alipanahi Babak
Published: June 2023

3051

Background: Orphan non-coding RNAs (oncRNAs) are a novel category of small RNAs (smRNAs) that are present in tumors and largely absent in healthy tissue. We investigated the utility of oncRNAs extracted from serum for early cancer detection across seven cancer types. Methods: We collected 2,882 serum samples from individuals with known cancers of the bladder ( n=152), breast (220), colon and rectum (141), kidney (283), lung (281), pancreas (287), and stomach (280) as well as donors with no history of cancer (1,238). We used 0.5 mL serum aliquots to generate and sequence smRNA libraries at an average depth of 20 million 50-bp single-end reads. Samples were split into age-, sex-, and smoking status-matched training (1,232 cancer; 922 control) and validation (412 cancer; 316 control) cohorts. A large catalog of oncRNAs specific to each cancer was created using tumor and adjacent normal samples from The Cancer Genome Atlas (TCGA) smRNA-seq database. Using TCGA-derived oncRNAs, we trained a machine learning model to predict cancer presence and tissue of origin (TOO) in a 5-fold cross validation setup using our training cohort. For the validation cohort, we averaged the predictions from the five training cohort models. Results: The model ROC-AUC for detecting cancer was 0.95 (95% CI: 0.94–0.95 for training and 0.94–0.97 for validation cohorts). Sensitivities for detecting cancer at 95% specificity were 0.74 (0.70–0.76) for early stage (I/II) and 0.80 (0.76–0.84) for late stage (III/IV) cancers in the training cohort, and 0.77 (0.71–0.81) and 0.81 (0.73–0.87) in the validation cohort. Sensitivities of detection for each cancer type are shown. For samples with cancer and TOO predictions, our top 1 and top 2 TOO accuracy was 0.76 (0.68–0.84) and 0.83 (0.76–0.90) for the validation set. Conclusions: These results demonstrate that oncRNAs detected in serum can be used for accurate, early detection, and localization of multiple cancers. [Table: see text]
NMR metabolomics in bladder cancer: Identification and monitoring of serum biomarkers during Pt-based treatment.
Authors: Giorgione Roberta , Gambale Elisabetta , Rossi Virginia , Mela Marinella Micol , Doni Laura , Roviello Giandomenico , Renda Roberta , Venturi Giulia , Pasqui Adriano , Zenoni Andrea , Bernini Andrea , Pillozzi Serena , Antonuzzo Lorenzo
Published: June 2023

3057

Background: To date, predictive and prognostic biomarkers for Bladder Cancer (BC) are lacking. Metabolomics, the study of small molecules involved in metabolism, aims to identify diagnostic, predictive and prognostic biomarkers. Overall, BC shows perturbations of various metabolic pathways, involved in biochemical reactions essential for energy production and for the maintenance of the REDOX balance, as well as in the metabolism of purines and pyrimidines. The main objective of this study is to characterize the serum metabolic profile of patients with BC undergoing platinum-based chemotherapy (Pt-CT), to identify the alterations induced by CT and evaluate the associated deregulated metabolic pathways, in order to identify potential biomarkers, prognostic and predictive of response to treatment. Methods: We enrolled patients with BC undergoing Pt-CT in different settings (neoadjuvant, adjuvant or metastatic). For each patient, a blood sample was collected before the start of each CT cycle (T0, T1, Tn). Metabolomic analysis was performed using the Bruker Avance 600 spectrometer. At baseline (T0), the metabolomic profiles of BC patients were compared with that of age- and sex-matched healthy controls. Major metabolites up- or down-regulated in patients with BC at baseline, were then monitored during CT (T1, Tn). Results: 14 patients were enrolled. When compared with age- and sex-matched healthy controls, patients with BC had elevated levels of acetate and acetone (ketone bodies), hypoxanthine, trimethylamine N-oxide (TMAO), glutamate, lactate, phenylalanine, and ornithine, and decreased levels of carnitine, choline, betaine, aspartate, threonine, 2-hydroxybutyrate, 2-aminobutyrate and histidine. When monitored during CT, hypoxanthine, glutamate, and aspartate levels increased; acetone, acetate and TMAO instead had a decreasing trend. Conclusions: The results of our pilot study confirm perturbations in several metabolic pathways: up-regulation of lactate, ketone bodies, hypoxanthine, phenylalanine, and glutamate levels in BC patients reflects altered glycolysis, fatty acid, purine, and amino acid metabolism, respectively. In addition, TMAO may play a role in the development of BC by promoting a pro-inflammatory and oxidative stress state. Furthermore, monitoring these metabolites could be a useful tool for predicting response to treatments. To our knowledge, there are no metabolomic studies that evaluated BC patients receiving CT and that included longitudinal monitoring to identify any changes in the metabolic profile induced by treatment.
Diagnostic application of circulating CDH17 biomarker for screening GI malignancies.
Authors: Ng Lui , Iyer Deepak , Wong Tony K , Hon Tsz Chun , Sun Stella , Luk John Moon , Foo Dominic Chi-Chung
Published: June 2023

3058

Background: Colorectal cancer (CRC) is the most common and treatable gastrointestinal (GI) cancer, yet it remains the second leading cause of cancer associated deaths globally. Cadherin-17 (CDH17) is a biomarker for GI cancers characterized by its overexpression in stomach, liver, and colorectal cancers but controlled expression in normal tissues from healthy adults. Although an improvement in the detection strategy of CDH17 is essential to apply it for large scale CRC screening. We have developed a novel diagnostic immunoassay using a panel of highly specific antibodies (PCT/US2019/032752) that unveiled CDH17 as a potential diagnostic maker with high detection sensitivity and specificity in CRC. Methods: The study recruited 150 patients (Retrospective specimens - 50 colorectal adenomas and 100 colorectal cancer) and 50 asymptomatic 18-80 years old blood donors (prospective specimens). CDH17 expression levels were measured within the individual blood-plasma samples using an enzyme-linked immunoassay. Results: The novel CDH17 diagnostic assay showed a wide operating dynamic range extending from 90ng to a lower limit of detection at 123pg. Using the assay, we observed a progressive and a significant increase in the plasma CDH17 concentration from the asymptomatic individuals to the colorectal adenoma group, while the CRC patients showed the highest expression of the circulating protein (median: 2.5ng/mL vs 4.5ng/mL vs 8.0ng/mL, P<0.0001). Within the CRC group, a higher CDH17 expression was associated with advanced tumor invasion, occurrence of nodal or distant metastases, as well as a clinical presentation of an advanced stage disease. The diagnostic power of the assay in terms of ROC AUC values was higher than 0.9 with an overall sensitivity of 82% that extended to 100% for metastatic CRC, while the specificity was at 94% for all stages combined (P<0.0001). Plasma CDH17 outperformed the clinically applied CEA and CA19-9 markers in differentiating the CRC patients from the asymptomatic population. Conclusions: The CDH17 immunoassay is potentially a diagnostics tool aid for the detection of CDH17 within blood samples prompting the early diagnosis of CRC. [Table: see text]
ctDNA analysis of NTRK fusion and mechanisms of acquired resistance to TRK inhibitors.
Authors: Sivaprakasam Karthigayini , Harada Guilherme , Choudhury Noura J. , Savin Casey , Shah Ronak H. , Berger Michael F. , Drilon Alexander E.
Published: June 2023

3062

Background: The regulatory approval of TRK tyrosine kinase inhibitors (TKIs) represented a landmark in tissue-agnostic drug development. Adult and pediatric patients harboring NTRK fusions derive meaningful clinical benefits from the first-generation TRK TKIs larotrectinib and entrectinib. However, characterizing NTRK fusions and resistance mechanisms to TRK TKIs by circulating tumor DNA (ctDNA) remains to be studied. Methods: Patients with NTRK-fusion-positive tumors who received TRK TKIs and had ctDNA analyzed using next-generation sequencing (NGS) were retrospectively identified. Samples were collected at multiple time points, including pre-TRK TKI, on-treatment, and post-progression. Mechanisms of resistance to TRK TKIs were examined when post-progression ctDNA samples were available. Results: Twenty-seven patients, with a median age of 57 years (range 28-81) and 11 different cancer types were identified. Twenty-two patients (81%; 22/27) had at least one ctDNA-positive sample (tumor burden greater than 0). A total of 67 ctDNA samples were analyzed by MSKCC ACCESS ctDNA pipeline, of which 10 samples (15%; 10/67) were collected before any TRK TKI. Forty-two samples (63%; 42/67) had positive ctDNA and NTRK fusion was detected in 16 ctDNA samples (24%; 16/67), including 9 (56%) NTRK1 fusions and 7 (44%) NTRK3 fusions. Among the pre-TRK TKI samples (n=10), 2 samples (20%, 2/10) had NTRK fusions detected. A total of 8 patients had post-progression samples with a resistance mechanism identified, of which 5 patients received larotrectinib and 3 entrectinib. The ctDNA samples revealed 7 patients (88%; 7/8) with on-target resistance and 1 patient (12%; 1/8) with off-target resistance. Among on-target mutations identified, the most common involved the solvent front residue (86%, n=6/7: n=2 NTRK3 G623R, n=2 NTRK1 G595R, n=1 NTRK3 G623E, n=1 NTRK3 623L) followed by the xDFG motif (14%, n=1/7: n=1 NTRK1 G667C). Regarding off-target alterations, one patient developed a BRAF V600E mutation. Conclusions: The use of plasma ctDNA can improve the identification of NTRK fusions through non-invasive techniques and potentially identify subsequent resistance mechanisms after the administration of the TRK TKIs.
Potential improvement in the diagnostic accuracy in detecting the estrogen receptor status in metastatic and recurrent breast cancer using 18F-FES PET/CT in the US.
Authors: Fuentes-Alburo Adolfo , DiGregorio Nicholas , Neeser Kurt , Jin Jiran , Young Regina
Published: June 2023

3063

Background: ER status helps classify BC for the most appropriate treatment pathway. Biopsy (Bx) and immunohistochemical (IHC) are established procedures to determine the ER status in metastatic BC (mBC, i.e., first occurrence of metastases) and recurrent BC (rBC, i.e., progression of mBC). In some cases, the accuracy of Bx/IHC to inform ER status may be challenged (e.g. difficult to access lesions; ER discordance within/across lesions and due to temporal heterogeneity; and when a Bx fails to obtain representative tissue). 16α-18F-fluoro-17β-fluoroestradiol (18F-FES) is a radiolabeled form of estrogen that binds to ER. For use with positron emission tomography /computed tomography imaging (PET/CT), it allows an assessment of whole-body ER+ status. In prospective trials and meta-analyses, 18F-FES PET/CT provided high diagnostic accuracy (DA) of ER+ disease. This study evaluated the potential increase in accuracy in determining ER+ status when 18F-FES PET/CT was added to IHC in mBC and rBC. Methods: An Excel based decision model was developed to estimate the impact on DA for ER+/HER2- US mBC and rBC patients over a five-year period by introducing 18F-FES PET/CT. The model assumed that 18F-FES PET/CT was added to Bx/IHC to classify ER status in three cases: (i) for mBC patients when Bx failed or was inconclusive, (ii) for mBC patients when Bx was not possible, or (iii) for all rBC patients. The DA between two scenarios was compared: scenario A, DA of Bx/IHC only and scenario B, 18F-FES PET/CT + Bx/IHC. Results: Scenario B, adding 18F-FES PET/CT, may lead to an increase in the initiation of appropriate endocrine- and chemotherapies, as defined by clinical practice guidelines, in all comparisons. The largest increase in DA was in rBC and, when BX is not possible, in mBC patients. Also, results indicate that introducing 18F-FES PET/CT decreases the number of re-biopsies performed except when Bx was not possible (ii). Conclusions: Adding 18F-FES PET/CT to Bx/IHC is expected to improve the DA of a patients’ ER status thereby increasing the information available to inform treatment, thus reducing the need for re-biopsies in mBC and rBC patients. By far the largest increase in DA of ER status using 18F-FES PET/CT was seen among patients with rBC (iii). [Table: see text]
Deep neural networks to predict pathological invasiveness through surgical resection images: A computer vision based prospective clinical trial in pulmonary nodules.
Authors: Yao Henian , Yao Lintong , Zhou HaiYu , Zhan Weijie , Daipeng Xie , Huang Zekai , Lin Hongwei
Published: June 2023

3068

Background: Pathological subtypes associate with surgical strategies of pulmonary nodule, during which thoracic surgeons make surgical decision through intraoperative frozen resection diagnosis. However, frozen section is time-consuming, vague and maybe misleading due to the limited sample and subjective judgements from pathologists. This study developed a predictive deep neural network for pathological invasiveness of pulmonary nodules based on the surgical resection images of gross specimens. Methods: We prospectively collected the specimen image under standardized lighting conditions in operating theaters from patients with pulmonary nodules treated by surgery resection from June 2020 to September 2021 in Guangdong Provincial People’s Hospital. Images were assigned into training cohort, validating cohort and test cohort as 8:1:1. With data augmentation, DenseNet was applied to classify the pulmonary nodules into high-risk and low-risk group. High-risk group was defined as grade 2 and grade 3 invasive pulmonary adenocarcinoma according to IASLC, while low-risk group was defined as adenocarcinoma in situ (AIS), minimally invasive adenocarcinoma (MIA) and grade 1 invasive pulmonary adenocarcinoma. Predictive efficiency was evaluated through area under the curve (AUC) of the receiver operating characteristic (ROC) curve, sensitivity, specificity, accuracy. Model performance would be compared with frozen section pathological diagnosis. Results: Among 1022 patients with pulmonary nodules enrolled, we have acquired 1080 images of the resected nodules in Guangdong Provincial People’s Hospital, with a mean age of 56 years and 39.1% of male patients. The median age of patients were 57 years in training cohort and 56 years in validating cohort, with 38.1% male patients in training cohort and 42.5% male patients in test cohort. This study included 864 images in training cohort, 108 images in validating cohort and 108 images in test cohort. Mean diameter of the nodules were 14.6mm in training cohort and 17.2mm in test cohort. In terms of predictive performance, the AUC value of ROC curves was 96.0% in training cohort and 95.0% in test cohort. In training cohort, the sensitivity of model was 97.6%, with the accuracy of 97.5% and specificity of 97.6%. In test cohort, the sensitivity of model was 97.6%, with the specificity of 90.2% and accuracy of 95.4%. Compared with frozen resection in testing cohort, our deep neural network had higher accuracy in pathological prediction (95.4% vs 88.9%). Conclusions: This study developed and validated a predictive algorithm on pathological invasiveness of pulmonary nodules through computer vision technique with highly sensitivity and specificity, which could assist the rapid evaluation for pathological invasiveness and intraoperative surgical decisions.
Multimodal machine learning analysis of more than 220,000 tumor profiles to diagnose molecular and morphological subtypes of cancer.
Authors: Abraham Jim , Klimov Sergey , Amidi Eghbal , Heimberger Amy B. , Marshall John , Heath Elisabeth I. , Drabick Joseph J. , Rubin Brian , Ali-Fehmi Rouba , Braxton David R. , Sledge George W. , Bryant David , Johnston Curtis , Ghani Hassan , Oberley Matthew James , Spetzler David
Published: June 2023

3078

Background: The diagnosis of a malignancy is typically informed by clinical presentation and tumor tissue features including cell morphology, immunohistochemistry, and molecular markers. Additionally, multi-omic approaches (Abraham 2021 Transl Oncol) and deep learning models using digital pathology (da Silva 2021 J Pathol) have augmented expert pathologists and led to improved diagnoses but are often not employed together on the same patient. The opportunity exists for a truly multimodal, multi-omic machine learning classifier that comprehensively assesses all aspects of a tumor from the molecular underpinnings to the morphological and histological phenotypic presentation to provide the most accurate diagnosis while at the same time providing predictive biomarker data from the same specimen. Methods: Whole transcriptome data from 220,246 tumor profiles, large panel and whole exome data from over 170,000 tumor profiles, and digital pathology features from over 50,000 tumors were used to construct a multi lineage classifier. The classifier was trained on 256 Oncotree classifications corresponding to established WHO diagnoses where a tumor of each class has been observed at least 30 times in our dataset. The dataset was split 50% for training and the other 50% for testing, UMAP was employed for dimensionality reduction, and ensemble models were used for making the final calls. The performance of the classifier was evaluated by comparing with traditional pathologist-directed diagnostic workup. Results: Tumor lineage classifiers predicted the correct classifications where the primary site was known with accuracies ranging between 97% and 100% when using the 32 highest level Oncotree categories corresponding to human tissues. Accuracy on the most granular Oncotree categories varied with many between 90 and 95%. When applied to Cancer of Unknown Primary (CUP) cases (n = 3589), an unequivocal Oncotree classification could be obtained over 90% of the time. Conclusions: Combining multi-omic and digital pathology information into a multimodal artificial intelligence platform can provide comprehensive information to pathologists to aid in diagnosis. This tool can be used to meet an unmet clinical need to define the lineage of CUP cases, which when coupled with biomarker data, will provide an opportunity to examine whether this information can be used to improve the outcomes of patient with CUP.
CBX-12-101: A first-in-human study of CBX-12, an alphalex peptide drug conjugate (PDC) in patients (pts) with advanced or metastatic solid tumors.
Authors: Rodriguez Rivera Ildefonso I , Hafez Navid , Tolcher Anthony W. , LoRusso Patricia , Wilks Sharon , Tripathy Debu , Gara Michelle , Pearson Paul , DeCillis Arthur P. , Meric-Bernstam Funda
Published: June 2023

3087

Background: Tumor-targeted drug delivery technologies are urgently needed to overcome conventional chemotherapy’s lack of tumor selectivity. Alphalex conjugates, which contain a pH-low insertion peptide (pHLIP), a linker and a payload, are designed to overcome this lack of selectivity. Unlike antibody drug conjugates, alphalex PDCs target tumors in an antigen-agnostic manner. At pH ≥7.0, the peptide is unstructured. In the low-pH tumor microenvironment the peptide forms an alpha helix and inserts directionally into the tumor cell membrane delivering the linker and payload intracellularly where the linker is cleaved releasing the payload in the cytosol. CBX-12 consists of the pH-sensitive peptide, a self-immolating linker, and the topoisomerase 1 (TOP1) inhibitor exatecan. Methods: In this Phase 1 trial, cohorts of pts were treated with escalating doses of CBX-12 in a 3 + 3 design on three dosing schedules: daily x 5 every 3 weeks, daily x 3 every 3 weeks or once weekly. The primary objectives are safety, tolerability and to determine the MTD and/or RP2D. Secondary and exploratory objectives include evaluation of plasma PK of CBX-12 and exatecan, anti-tumor activity per RECIST v1.1, and measurement of anti-drug antibodies. Results: As of 26 Jan 2023, 42 pts have been treated on three schedules. The most frequent treatment-related AEs (TRAEs) were anaemia (42.9%), nausea (38.1%), fatigue (33.3%), ANC and WBC decreased (33.3% each), vomiting (26.2%), diarrhoea (23.8%) and thrombocytopenia (19.0%). The most frequent Gr3/4 TRAEs were ANC decreased (28.6%), anemia (23.8%), WBC decrease (16.7%), thrombocytopenia (14.3%). Dose limiting toxicity was observed in 6 pts: myelosuppression (6 pts) febrile neutropenia (2 pts), and sepsis (2 pts). Responses were observed in 2 of 9 pts with ovarian cancer and 2 of 8 with breast cancer. The MTD on the daily x 3 schedule is 45mg/m2. Dose evaluation continues on the weekly schedule. Conclusions: In this FIH study of a pH-targeting alphalex PDC, CBX-12 demonstrated single-agent antitumor activity including 4 responses with the dominant toxicity of myelosuppression. Phase 2 expansion cohorts are planned in pts with platinum-resistant ovarian cancer and hormone-receptor positive, HER2 negative breast cancer. Clinical trial information: NCT04902872 .
EZH2/EZH1 inhibitor tulmimetostat (CPI-0209) in patients with advanced solid tumors or hematologic malignancies: Preliminary phase II results.
Authors: Drescher Charles , Walter Harriet S. , Gastinne Thomas , Lakhani Nehal J. , Ribrag Vincent , Rasco Drew W. , Gutierrez Martin , Sullivan Ryan J. , Harvey R. Donald , Banda Kalyan , Kwiatek Michal , Garcia-Sancho Alejandro Martin , Duska Linda R. , Zinzani Pier Luigi , Thakur Anjali , Kann Lennart , Faulhaber Nicola , Jauch-Lembach Julia , Kindler Hedy L.
Published: June 2023

3094

Background: Many preclinical tumor models with mutations in ARID1A and BAP1 are highly sensitive to EZH2 inhibition. Tulmimetostat (CPI-0209) is an investigational oral, next-generation, dual EZH2/EZH1 inhibitor with durable target coverage. Phase I dose escalation established a recommended Phase II dose of 350 mg (Lakhani et al. ASCO 2021). We report preliminary Phase II findings from the ongoing Phase I/II study (NCT04104776). Methods: Phase II is evaluating tulmimetostat 350 mg once daily in 28-day cycles in 6 disease-based cohorts (Table). The Simon 2-stage study design requires 1 response (complete [CR] or partial [PR]) in stage 1 (n = 10 patients [pts]) for expansion to stage 2 (plus n = 19) (except in M4, see table). Primary endpoint is objective response rate (ORR) based on disease-specific criteria; secondary objectives include safety. Results: As of Nov 08, 2022, 62 pts received ≥1 dose (safety evaluable); 48 had ≥1 postbaseline tumor assessment (efficacy evaluable). Pts had median 3.2 years (0.6–19.6) since diagnosis; 77.4% had ≥2 prior lines of therapy. Cohorts M2, M5 and M6 had completed stage 1 enrollment. At cut-off, best responses among evaluable patients (Table) show 4 cohorts have at least 1 confirmed response, including 2 CR and 1 PR in 7 pts with peripheral T-cell lymphoma (PTCL). 47 pts (75.8%) experienced TEAEs leading to dose modifications, 20 (32.3%) had serious TEAEs, and 5 (8.1%) discontinued treatment due to TEAEs. The most frequent TEAEs (≥15% of pts) (any Grade/Grade ≥3) considered at least possibly related to tulmimetostat were thrombocytopenia (51.6%/27.4%), diarrhea (45.2%/12.9%), nausea (37.1%/0%), anemia (30.6%/16.1%), fatigue (29.0%/0%), alopecia (25.8%/1.6%), dysgeusia (24.2%/0%), vomiting (21.0%/0%), and neutropenia (17.7%/14.5%). Conclusions: Based on response criteria of ORR ≥1/10 pts, the ovarian (M2), endometrial (M3), and mesothelioma (M5) cohorts achieved eligibility for stage 2 expansion (not relevant in M4). The safety profile of tulmimetostat is consistent with EZH2 inhibition and previous data. These preliminary findings in heavily pretreated pts with multiple tumor types, including tumors with ARID1A alterations or BAP1 loss, support ongoing investigation of tulmimetostat. Clinical trial information: NCT04104776 . [Table: see text]
Dose optimization of novel BRAF inhibitor FORE8394 based on PK and efficacy results.
Authors: Sherman Eric Jeffrey , De La Fuente Macarena Ines , Yaeger Rona , Tsai Frank Yung-Chin , Janku Filip , Butowski Nicholas A. , Allen Carl E. , Ammakkanavar Natraj Reddy , Taylor Jennie Webster , Samara Emil , Mould Diane R. , Michelson Glenn , Kline Irina , Paz Michael , Tussay-Lindenberg Alexia , Wong Kongming , Shepherd Stacie Peacock , Jiang Ping , Rodon Ahnert Jordi
Published: June 2023

3106

Background: FORE8394 is a selective inhibitor of class 1 (V600) and 2 (activating non-V600) BRAF alterations that avoids paradoxical MAPK pathway activation. Consistent with the paradigm shift to optimal dosing vs identifying the maximal tolerated dose, integrated pharmacokinetic (PK), genomics, safety, and efficacy data, and exposure-response modeling were used to identify the recommended dose (RD). Methods: In a single arm phase 1/2a study, patients (pts) age ≥3 years with advanced solid or CNS tumors with BRAF alterations received FORE8394 900-3600 mg/day with or without the PK enhancer cobicistat (cobi) until progression. Efficacy pts had class 1 or 2 BRAF alterations & ≥1 post-baseline assessment (mITT); the BRAF V600 MAPKi naïve, non CRC subset provided a homogenous subset to also inform dose selection. PK was evaluated after single and repeated dosing. Results: To date, 110 pts (age range 4-86 years) received ≥1 dose of FORE8394; 58% had ≥2 prior lines of therapy, 25% had prior MAPKi. PK was independent of age or weight. Cobi increased FORE8394 exposure 2-3-fold. Exposure increased with dose, with less than proportional increase at doses >900 mg BID. Higher Cmax and trough levels were achieved with QD vs BID/TID. Objective (confirmed) responses were observed at all doses; however, objective response rate (ORR) was greatest (50%) at 900mg QD + cobi, with no further increases in ORR at higher doses. Dose-limiting toxicities were only observed at doses ≥1500 mg/day + cobi: 1500-1800 mg/day (4) and 2700-3600 mg/day (1). Similarly, treatment-emergent adverse events (TEAEs) ≥Grade 3 (G3) increased at the higher doses. Only 1 pt discontinued FORE8394 due to treatment-related AE (G3 bilirubin; 3600 mg/day). Conclusions: Based on the entirety of safety, PK, and efficacy data, the optimal RD of FORE8394 in Phase 2 is 900 mg QD + cobi in pts ≥10 years old. This achieved targeted efficacious exposures with robust antitumor activity and favorable safety. This dose optimization is consistent with current guidelines, avoids higher exposure that may lead to higher toxicity and compromise dose intensity. QD dosing also allows for a convenient dosing regimen. A Phase 2 study at the RD is ongoing in pts with recurrent V600E BRAF-mutated primary CNS tumors and advanced solid or CNS tumors with BRAF fusions. Clinical trial information: NCT02428712 . [Table: see text]
Impact of patient travel time on disparities in precision oncology clinical trials.
Authors: Uehara Yuji , Koyama Takafumi , Katsuya Yuki , Sato Jun , Yamamoto Noboru
Published: June 2023

3113

Background: Precision oncology revolutionizes cancer care, allowing personalized treatments to improve outcomes. Precision oncology often entails participation in genotype-matched clinical trials, resulting in referrals from institutions providing comprehensive genomic profiling (CGP) testing to those conducting these trials. It is still being determined whether there are regional disparities in precision oncology. Methods: We conducted a retrospective review of 1127 patients (pts) referred to National Cancer Center Hospital (NCCH) for participation in genotype-matched clinical trials following CGP testing performed between June 2020 and June 2022. Travel distance and time were calculated utilizing Google Maps from the patient's residence to the NCCH. A total of 23 covariates were preselected and dichotomized per previous research or expert consensus as follows: age, sex, performance status, body mass index, tumor type, number of lines of prior therapies, number of metastatic sites, liver metastases, brain metastases, pleural or peritoneal effusions, biopsiability, neutrophil, hemoglobin, platelet, albumin, creatinine, total bilirubin, LDH, AST, CRP, place of residence (urban vs. rural), referring hospitals, and household income. All independent variables associated with participation in genotype-matched trials (P < 0.20) were included in a multivariable model, and variable importance was calculated using a machine learning (ML) model (gradient-boosted decision tree). Results: A total of 127 (11%) of 1127 pts were enrolled in the genotype-matched trials. Of 127 pts, 82 (65%) and 45 (35%) participated in phase 1 trials and phase 2/3 trials, respectively. The overall median travel distance and time were 38 km (interquartile range [IQR] 21–107) and 55 minutes (IQR 35–110), respectively. In multivariable regression, travel distance (≥100km vs. <100km) was not associated with the proportion of genotype-matched trial participation (9% vs. 12%; odds ratio [OR], 0.68; 95% confidence interval [CI], 0.42–1.07; P = 0.11); however, in pts with travel time ≥120 minutes, the proportion of genotype-matched trial participation was significantly lower than those with travel time < 120 minutes (7% vs. 13%; OR, 0.54; 95% CI, 0.32–0.89; P = 0.019). The proportion of genotype-matched trial participation decreased as travel time increased from <40 minutes to 40–120 minutes to ≥120 minutes (13% vs. 12% vs. 7%, respectively; OR, 0.67; 95% CI, 0.50–0.88; P = 0.006). Travel time was also identified as an important factor in the ML model, whereas low-income and residence in rural areas were of minor importance. Conclusions: Patients with travel time ≥120 minutes were less likely to participate in genotype-matched clinical trials than those with travel time <120 minutes. Regional disparities may be creating inequities in precision oncology, which warrant immediate action, including decentralization of clinical trials.
Temsirolimus (T) in patients (pts) with solid tumors with PIK3CA mutation (mut): Results from the Targeted Agent and Profiling Utilization Registry (TAPUR) study.
Authors: Calfa Carmen Julia , Rothe Michael , Srkalovic Gordan , Duvivier Herbert Leon , Behl Deepti , Straughn J Michael , Yost Kathleen J , Mehmi Inderjit , Pisick Evan P. , Sharma Bhavina B , Thota Ramya , Veljovich Dan Steven , Alese Olatunji B. , Cannon Timothy Lewis , Gaba Anu G. , Urba Walter John , von Mehren Margaret , Grantham Gina N. , Halabi Susan , Schilsky Richard L.
Published: June 2023

3117

Background: TAPUR is a phase II basket study evaluating antitumor activity of commercially available targeted agents in pts with advanced cancers with genomic alterations. Results in cohorts of pts with breast cancer (BC) and other solid tumors with PIK3CA mut treated with T are reported. Methods: Eligible pts had BC or other solid tumors, measurable disease, ECOG performance status (PS) 0-2, adequate organ function, and no standard treatment (tx) options. Genomic testing was performed in CLIA-certified, CAP-accredited site selected labs. After antihistamine pre-tx, 25 mg of T was infused over 30-60 minutes once weekly until disease progression. Primary endpoint was disease control (DC), defined as complete or partial (PR) response, or stable disease of at least 16+ weeks (wks) duration (SD16+) per RECIST v1.1. For the BC cohort, Simon’s optimal 2-stage design with null DC rate of 15% vs. 35% (power=0.85, α=0.10) was used with stage 1 (n=10) stopping for futility if < 2/10 pts had DC. Low accruing histology-specific cohorts with PIK3CA and T tx were collapsed into 1 histology-pooled (HP) cohort. For the HP cohort, the hypothesized null DC rate of 15% was evaluated by a 1-sided exact binomial test with α=0.10. Secondary endpoints were progression-free survival (PFS), overall survival (OS), and safety. Results: 12 pts with PIK3CA mut with BC and 29 pts with PIK3CA mut in other solid tumors (across 9 tumor types) were enrolled. 2 pts (1 in each cohort) were found to be ineligible after enrolling and were not included in efficacy analyses. Demographics and outcomes for each cohort are shown. At the end of stage 1 in the BC cohort, 1 PR was observed for DC and OR rates of 9%; the cohort was closed for futility (p=0.83). For the HP cohort, 3 PR and 5 SD16+ were observed for DC rate of 29% (p=0.049) and OR rate of 11%; the null hypothesis was rejected. Cancer types in pts with OR or SD16+ included cervical, ovarian and head/neck; most common muts were H1047R/L (3), E545K (2) and E542K (2). 1 pt with ovarian and H1047R has ongoing PR at 86 wks. 11/41 pts had ≥1 tx-related grade 3-4 adverse or serious adverse event, including anemia, headache, hyperglycemia, hypertension, hypertriglyceridemia, mucositis oral, lymphocyte, neutrophil or platelet count decrease, pneumonitis, and sepsis. Conclusions: Although T does not appear to have antitumor activity in pts with BC with PIK3CA mut, it does show antitumor activity in pts with other solid tumors with PIK3CA mut and warrants further study. Clinical trial information: NCT02693535 . [Table: see text]
Pan-cancer diagnostic proteomic signature of tissue-of-origin (TOO) using data-independent acquisition mass spectrometry (DIA-MS) from 1289 human tissue samples.
Authors: Boys Emma , Liu Jia (Jenny) , Cai Zhaoxiang , Noor Zainab , Mackenzie Karen L , Aref Adel , Sykes Erin , Xavier Dylan , Lucas Natasha , Williams Steven , Bucio-Noble Daniel , Koh Jennifer , Hains Peter , Robinson Phillip J , Zhong Qing , Reddel Roger R
Published: June 2023

3120

Background: Accurate tumour classification based upon tissue of origin (TOO) remains important to guide treatment selection and prognosis but can be challenging in patients with poorly differentiated malignancy, cancer of unknown primary (CUP) or those with prior malignancy. Data-independent acquisition mass spectrometry (DIA-MS)-based proteomics is emerging as a potential clinical diagnostic and prognostic tool. We aimed to develop a protein-based signature to identify histological subtype and adenocarcinoma TOO using DIA-MS data obtained from a pan-cancer study of human tissue samples as an adjunct to histopathological assessment in challenging clinical scenarios. Methods: We performed DIA-MS-based proteomic profiling of 795 fresh frozen tumour and 494 tumour-adjacent normal samples from the Victorian Cancer Biobank in a clinically orientated workflow. We filtered the cohort to include tumour types relevant to CUP. Protein quantification was derived from raw peptide intensity data. Random forest classifiers to identify histological subtype and adenocarcinoma TOO were subsequently trained and tested using 70% and 30% of the data respectively. Evaluation metrics included top-k accuracy (predicting how often the correct class is among the top k predicted classes) and area under the receiver operating curve (AUROC) (one-versus-rest) ± 95% confidence interval. Results: The final tumour cohort consisted of 427 tumour samples representing eight histological subtypes (adenocarcinoma, germ cell tumour, lymphoma, melanoma, renal cell carcinoma, sarcoma, squamous cell carcinoma, thyroid carcinoma) and seven adenocarcinoma TOO (breast, colorectal, liver, lung, ovary, pancreas, prostate). From 9,051 quantified proteins, 83 were identified with potential utility at identifying histological subtype and adenocarcinoma TOO for use in machine learning models. The histological subtype model identified cancer subtype in the test set with top-1 and top-2 accuracy of 0.95 ± 0.03 and 0.98 ± 0.02 respectively. Average test AUROC over all cancer types (n=8) was 0.98 ± 0.02. The adenocarcinoma TOO model identified tumour TOO in the test set with top-1 and top 2- accuracy of 0.88 ± 0.07 and 0.95 ± 0.04 respectively. Average test AUROC over all adenocarcinoma TOO (n=7) was 0.97 ± 0.02. Conclusions: Our clinically orientated DIA-MS-based proteomic workflow and supervised machine learning can identify protein signatures that classify histological subtype and TOO in tumour samples with high accuracy. This technology may assist diagnostic classification of cancer in challenging clinical scenarios, such as CUP.
Characterizing telomerase reverse transcriptase (TERT) promoter mutations (mut) across sex, race, and cancer types.
Authors: El Zarif Talal , Machaalani Marc , Nawfal Rashad , Xie Wanling , Choueiri Toni K. , Pomerantz Mark
Published: June 2023

3122

Background: TERT promoter mut. have been evaluated as a predictive biomarker for patients (pts) receiving immune checkpoint inhibitors. Understanding the prevalence of TERT promoter mut. by sex, race, and cancer type is essential for optimizing its use. Methods: Pts who underwent next-generation sequencing at Dana-Farber Cancer Institute and Memorial Sloan Kettering Cancer Center were identified from the AACR Genomics Evidence Neoplasia Information Exchange (GENIE) registry v11.0. Self-reported race and sex data were extracted for ten cancer types with the highest prevalence of TERT promoter mut. The strength of associations with TERT promoter mut. was quantified by Odds ratios (ORs) and two-sided Fisher’s exact tests, along with FDR-adjusted q-values using the Benjamini-Hochberg method. Results: We identified 31,925 pts – 87.6% (27,970) self-identified as White, 7.1% (2,273) Asian, and 5.3% (1,682) Black. TERT promoter mut. were present in 17% (5,470) tumors, including 56% (1,346/2,411) bladder cancers, 43% (966/2,243) melanomas, 41% (395/959) thyroid cancers, and 23% (183/782) head and neck cancers (HNC). TERT promoter mut. were significantly higher in males vs. females in melanoma, cancer of unknown primary (CUP), hepatobiliary (HPB), and thyroid cancers. In contrast, males harbored fewer mut. vs. females with HNC. Interestingly, TERT promoter mut. varied by race. Mut. frequency was significantly higher in White pts with melanoma (44%, n=964/2176) compared to Asian and Black pts (2.9%, n= 2/67) (OR=25.8; 95% CI = 6.9 - 217, p<0.0001). Asian males with HNC (37%, n= 22/60) were enriched for TERT promoter mut. vs. White males (19%, n= 93/489) (OR = 2.5; 95% CI = 1.4 - 4.4; q=0.03). Within HNC tumors, oral cavity (OC) tumors (44.3%, n= 85/192) were associated with higher TERT promoter mut. vs. other HNC subtypes (16.6%, n= 98/590) (OR = 4.4; 95% CI = 3.03 - 6.26; p<0.0001). Asian pts with OC (70%, n=14/20) harbored more mut. vs. White pts with OC (41.4%, n=70/169) (OR = 3.3; 95% CI = 1.2 - 9; p<0.05). Conclusions: Our study demonstrates differences in the distribution of TERT promoter mut. by sex, race, and cancer type. Considering these variations is crucial for future clinical trial design and biomarker studies. [Table: see text]