bluuebunny/crossref_metadata_2025 huggingface dataset:
Simultaneous detection of tumor-derived mutations in DNA and RNA extracted from a single circulating tumor cell based on droplet digital polymerase chain reaction.
Authors: Choi Jaesung , Park Sehwan , Jeong Aejin , Kim Hanbyeol , Pak Sehyung , Song Min-Ji , Kim Jungwon , Lee Hai-Chon
Published: June 2024

e15053

Background: Androgen receptor splice variant 7 (AR-V7) is a constitutively activated isoform of AR and has been associated with resistance to AR-targeted therapies and development of metastatic castration-resistant prostate cancer. Confirmation of AR-V7 expression is important step in prostate cancer diagnosis and determining the appropriate drug, however, the detection of AR-V7 with tissues has limitations, such as the clinical challenge to poorly accessible tumor tissues before and after therapy. In addition, KRAS mutations serve as a prognostic biomarker for the administration of appropriate anti-cancer drugs in patients with various cancers, including non-small cell lung cancer (NSCLC). Here, we developed the process for the simultaneous detection of AR-V7 and KRAS mutation in CTCs using isolation with CytoGen’s Smart Biopsy™ System with droplet digital polymerase chain reaction (ddPCR) with high sensitivity and specificity, overcoming the limitations of tissue biopsy. Methods: ddPCR assays were performed to detect the KRAS G12C mutation using CTC gDNA and to evaluate the absolute levels of AR-V7 using CTC mRNA. Analytical validation was performed using NSCLC NCI-H358 and prostate cancer 22Rv1 cells (10 and 5 cells each), which harbor KRAS G12C and AR-V7, respectively, spiked into 5 mL of healthy blood to mimic CTC. CTCs were isolated using CytoGen's Smart Biopsy™ System. Oligo-dT magnetic beads were used to isolate mRNA from CTCs, and gDNA was isolated from the mRNA-depleted CTC lysates using the AllPrep DNA/mRNA Nano Kit. PCR and droplet reading for each assay were performed on the QX200 AutoDG Droplet Digital PCR System. Results: As a result of CTC KRAS G12C detection using the ddPCR™ KRAS G12/G13 Screening Kit, the mutated KRAS gene was successfully detected in as few as 5 NCI-H358 cells. In the results of CTC AR-V7 detection using the custom TaqMan ddPCR assay, transcripts (AR-V7 and HPRT1) were successfully detected even with only 5 22Rv1 cells. These results suggest that CytoGen's Smart Biopsy™ System could be applied to the simultaneous detection of DNA/RNA mutated genes in clinical NSCLC and prostate cancer patients with detection technology requiring high sensitivity and specificity. Conclusions: Accurately detecting multiple genetic mutations in CTCs is a challenging because CTCs are very rare in the blood. In this study, we developed the process to simultaneously extract and detect DNA mutations and RNA splicing variants in CTCs using CytoGen's Smart Biopsy™ System. This process, along with the results from our ongoing clinical trials, could provide information for the diagnosis and appropriate treatment of patients with various cancers, including NSCLC and prostate cancer.
Multidimensional tumor profiling and its meaningful impact on personalized therapy outcomes: Insights from a real-world study.
Authors: Schaffrin-Nabe Dorthe , Crook Tim , Limaye Sewanti , Schuster Stefan , Josten-Nabe Anke , Reismann David , Patil Darshana , Datta Vineet , Heinze Adrian , Schaffrin Merle , Voigtmann Rudolf , Kurzrock Razelle
Published: June 2024

e15064

Background: This real-world study underscores the transformative potential of multidimensional tumor profiling, including tissue and blood-based markers, in guiding personalized oncology treatments. We established a robust link between comprehensive diagnostics and improved clinical outcomes by correlating extensive profiling data with progression-free survival (PFS), the ratio of PFS2 to PFS1, and comparing these with treatment modalities. Methods: Over five years, 44 patients with advanced-stage solid tumors underwent comprehensive tumor profiling, including genetic markers from tissue and blood, mRNA expression, circulating tumor cells, pharmacogenomics, and immunohistochemistry, to tailor therapies. These multidimensional datasets were rigorously analyzed applying machine learning algorithms against responses to target, chemo, and combo therapies, using robust statistical frameworks to elucidate the impact of advanced diagnostics on therapy effectiveness. Results: Multidimensional tumor testing markedly extended progression-free survival, with median PFS1 and PFS2 at 22.5 and 30 weeks, respectively t(43) = 1.76, p = 0.043, and a significant median PFS2/1 ratio of 1.31. Targeted therapies achieved the highest median PFS2 at 61 weeks, surpassing chemo alone (10.5 weeks) and combination therapy (29.5 weeks) significantly. Patients treated based on gene expression, including mRNA profiling and immunohistochemistry/immunocytochemistry (n = 22), had a median PFS of 37.5 weeks, outperforming those treated based on NGS (n = 12) with 27.5 weeks significantly. Those not fully adhering to guideline treatments due to divergent findings had a median PFS2 of 16.5 weeks. Notably, 26 out of 44 patients with critical illness had a PFS2 over 6 months. Conclusions: A clear linkage was established between comprehensive profiling indicators, including genetic, molecular, and cellular markers, and the observed therapeutic outcomes. The study reaffirms the critical importance of multidimensional tumor profiling in the era of precision oncology. However, we proceed monitoring this growing group of patients to establish a clearer picture how to adapt complex diagnostic tools into modern oncological practice.
Role of artificial intelligence in ocular tumors: A systematic review.
Authors: Farabi Maleki Shadi , Yousefi Milad , Hajiesmailpoor Zanyar , Jafarizadeh Ali , Pedrammehr Siamak , Alizadehsani Roohallah , Gorriz Saez Juan Manuel
Published: June 2024

e15070

Background: Integrating oncology and artificial intelligence (AI) shows significant potential in improving treatments and early detection of ocular tumors. This systematic review aims to strengthen existing evidence regarding the application of AI in diagnosing and treating ocular tumors. Methods: We systematically searched PubMed, Embase, Web of Science, Scopus, and Google Scholar until January 15, 2024. Inclusion criteria comprised original peer-reviewed human studies (retrospective or prospective) investigating AI approaches in patients with ocular tumors such as retinoblastoma, uveal melanoma, conjunctival melanoma, and choroidal melanoma. The quality of the literature was assessed using JBI checklists. The eligibility criteria involved assessing studies that explored the application of AI in ocular tumor detection, classification, and treatment planning. We employed a rigorous screening process, and subsequent data extraction focused on key characteristics, including tumor types, sample sizes, AI input data specifications, and study aims. Exclusion criteria encompassed studies not meeting the inclusion criteria, lacking relevant outcome measures, exhibiting insufficient methodological quality, or inadequate reporting. Results: The initial database search yielded 903 records, of which 37 studies (retrospective = 24 and prospective = 13) were included. Most studies selected the retinoblastoma (n = 12) and uveal melanoma (n = 14). Other studies utilized other types of ocular tumors, including ocular metastasis (n = 2), ocular surface squamous neoplasia (n = 2), and ocular lymphoma (n = 2). The conjunctival melanoma, choroidal melanoma, intraocular melanoma, cavernous hemangioma, and schwannoma patients were utilized once. The AI-based models were employed for the classification (n = 22), prognosis prediction (n = 6), lesion segmentation (n = 5), and predicting the gene expression (n = 4) tasks. The data types used Included magnetic resonance imaging (MRI), computed tomography (CT), whole-slide imaging (WSI), clinical data, and fundus images. A meta-analysis was precluded because of the significant heterogeneity observed across the included studies in terms of demographics, study design, interventions, and outcome measures. Conclusions: Although imaging and patient presentation have played a crucial role in ocular tumor diagnostics, AI presents promising results in prediction, prognosis, and disease management. Meanwhile, AI's primary role has been in classification, demonstrating significant success. Additionally, continued exploration of less-discussed eye tumors is essential for enhancing AI's predictive and therapeutic capabilities. The absence of reported evaluation criteria and low evaluation parameter rates in certain studies underscores the importance of standardized reporting practices for robust assessments in future ocular oncology research.
Unraveling the role of ubiquitin C-terminal hydrolase L1 in high grade serous ovarian cancer pathogenesis.
Authors: Jansen Corinne , McAdams Julia , Woodman Morgan , De La Cruz Payton , Grive Kathryn , James Nicole
Published: June 2024

e15078

Background: High grade serous ovarian cancer (HGSOC) is the most lethal of all gynecologic malignancies, due to the fact that the majority of patients are diagnosed at an advanced stage and eventually develop chemoresistant disease 12-18 months following completion of frontline therapy. Therefore, novel targeted therapies are urgently needed to combat chemoresistance and improve patient clinical outcomes. Ubiquitin C-terminal hydrolase L1 (UCHL1) is a deubiquitinating enzyme that plays a vital role in protein homeostasis and is highly overexpressed in HGSOC. It was previously uncovered that targeting UCHL1 with small molecule inhibition reduced cell viability in a chemoresistant ovarian cancer cell line. Methods: Comparative-label free proteomic analysis was used to uncover significant changes in HGSOC cell line OVCAR8WT following treatment with UCHL1 small molecule inhibitor, LDN-5744 or corresponding DMSO control. Significant pathway changes were determined by KEGG analysis. Matched chemosensitive and resistant HGSOC cells PEA1 and PEA2 were treated in combination with LDN-5744 and carboplatin, with cell viability was determined by an MTS assay. Furthermore, western blot analysis was employed to compare common cell growth pathway changes as a result of UCHL1 inhibition in HGSOC cells. Results: Proteomic analysis revealed a significant (p<0.05) upregulation in methyl phosphate capping enzyme (MEPCE) (4.9-fold), asparagine synthetase (ASNS) (2.5-fold), Phosphoserine aminotransferase 1 (PSAT1) (1.7-fold), and downregulation in centrosomal protein 55 (CEP55) (-7.2-fold), These identified proteomic changes were confirmed by western blot. KEGG pathways analysis using all significantly (p<0.05) differentially expressed proteins showcased significant (p<0.05) enrichment in amino acid biosynthesis, and metabolism, and chemical carcinogenesis-reactive oxygen species. Chemoresistant PEA2 cells treated in combination with LDN-5744 and carboplatin demonstrated a 59% reduction in cell viability, significantly (p<0.001) lower than the 13% and 22%, that was observed from UCHL1 and carboplatin treatment alone, respectively. Conversely, PEA1, the chemosensitive counterpart to PEA2 demonstrated a significant (p<0.001) 37% increase in cell viability upon combinatorial treatment compared with carboplatin alone, indicating that UCHL1 inhibition rescues the cells from chemotherapy induced cell death. Finally, LDN-5744 treatment in PEA2 led to a reduction in levels of phospho-(p-)AKT, p-STAT3, and p-ERK, while conversely in PEA1 cells levels of these proteins were increase or unchanged. Conclusions: Our findings demonstrate that targeting UCHL1 results in prominent metabolic changes in HGSOC cells and that the efficacy of UCHL1 inhibition is heavily dependent upon platinum status. Overall, this study highlights UCHL1’s novel therapeutic role in the recurrent HGSOC.
Results of a first-in-human, dose-escalation phase 1 study of the ERK1/2 inhibitor ATG-017 in patients with advanced solid tumors.
Authors: Wahlroos Sara , Teng Christina , Tran Ben , Voskoboynik Mark , Gan Hui Kong , Spencer Andrew , Kudva Anupa , Song Ming , Lynch Kevin , Yu Zhinuan , Desai Jayesh , Lemech Charlotte Rose
Published: June 2024

e15114

Background: This open-label, first-in-human, phase 1 study evaluates the safety, pharmacokinetics, and maximum tolerated dose (MTD) of ATG-017, an oral, potent, and highly selective inhibitor of ERK1/2, in patients with refractory advanced solid tumors. Methods: Twenty-one patients with solid tumors harboring activating alterations in the RAS-MAPK pathway were enrolled in the 3+3 design dose-escalation phase for continuous dosing: 5 mg QD (n=1), 5 mg BID (3), 10 mg BID (3), 20 mg BID (7), 30 mg BID (4), and 40 mg BID (3). Results: Safety: All patients reported at least 1 treatment-emergent adverse event (TEAE). Fourteen patients (66.7%) experienced serious adverse events. At 40mg BID, 2 of 3 patients experienced a dose-limiting toxicity (DLT) (grade 3 diarrhea and grade 3 retinopathy). At 30mg BID, 2 of 4 patients experienced a DLT (grade 3 acneiform dermatitis and grade 2 blurred vision). All DLTs resolved with drug interruption. At 20mg BID, a potentially biologically active dose, 7 patients were treated with no DLTs observed. At all dose levels, the most commonly observed TEAEs were consistent with previously reported toxicities with other ERK pathway inhibitors (gastrointestinal, skin, and ocular adverse events). Pharmacokinetics: Between 5mg BID and 30mg BID, exposure increased proportionally. At doses 20mg BID or higher, the concentration in the whole dosing interval (≥ 328ng/mL, geometric mean) was higher than the target concentration (231 ng/mL) for effective ERK inhibition derived from preclinical PK/PD models. Efficacy: Of the 21 treated patients, one patient (4.8%) with mesonephric-like ovarian adenocarcinoma (KRAS G12V mutation) in the 30 mg BID cohort achieved a best response of partial response (sustained for six cycles of treatment), and 8 (38%) patients were assessed as having stable disease (sustained over an average of five cycles), based on RECIST v1.1. Conclusions: In patients with solid tumors, 20mg BID continuous dosing of ATG-017 was identified as the MTD and delivers exposure that is likely to be active in inhibiting ERK. This dose is currently being explored in a dose expansion phase. A combination regimen with nivolumab is also being investigated. Clinical trial information: NCT04305249 .
Efficacy and safety of surufatinib combined with EP regimen and serplulimab in first-line treatment of NEC.
Authors: Zhang Tao , Lin Zhenyu , Zhao Lei , Ma Hong , Zhang Dejun , Yu Dandan , Jin Min , Wang Jing , Liu Hongli
Published: June 2024

e15123

Background: Neuroendocrine carcinomas (NEC) are more challenging than neuroendocrine tumors (NET) due to poor differentiation, aggressive invasion, and early diagnosis difficulties, often marked by local and distant metastasis at diagnosis, leading to poor outcomes. The ORR for NEC as first-line treatment with EP or EC regimens is approximately 30%, highlighting a substantial treatment gap. Surufatinib, a targeted small molecule kinase inhibitor, acts on vascular endothelial growth factor receptors (VEGFR-1/2/3), fibroblast growth factor receptor (FGFR-1), and colony-stimulating factor-1 receptor (CSF-1R). Its efficacy focuses on anti-angiogenesis and vascular normalization, alongside its role in modulating tumor-associated macrophages (TAMs) and boosting the effectiveness of immunotherapy. Methods: This single-arm, open-label, multicenter clinical study comprised a safety run-in (SR) phase and a dose-expansion (DE) phase. In the SR phase, six patients (pts) were planned to be enrolled to receive treatment with surufatinib (250 mg, QD, PO, Q3W) combined with the EP regimen (etoposide injection: 100mg/m2, d1-3, IV, Q3W; cisplatin: 25mg/m2, d1-3, IV, Q3W) and serplulimab (300mg, d1, IV, Q3W) for a maximum of six cycles, followed by a maintenance phase of surufatinib plus serplulimab until disease progression or other criteria as specified in the protocol. The dose of surufatinib in the DE phase was based on results from the SR phase. The primary endpoints were recommended Phase 2 dose (RP2D) and PFS, while secondary endpoints included ORR, DCR, OS, and safety. Results: As of December 27, 2023, this reports results from the SR phase. Six pts, median age 61.5 years (range 38-70), 66.7% male, all with ECOG performance status 1, were enrolled and completed their first treatment cycle. A majority (83.3%) had gastrointestinal-origin tumors with a median Ki-67% index of 70% (range 30%-90%). During the SR phase, one patient experienced Grade 4 hematologic toxicity (neutropenia and leukopenia) as a dose-limiting toxicity (DLT). Consequently, RP2D of surufatinib was established at 250mg for further research in the DE phase. The most common adverse events were neutropenia (50%), decreased white blood cell count (33.3%), fatigue (33.3%), and diarrhea (33.3%). Among those enrolled in the SR phase, 5 pts underwent at least one assessment of efficacy, yielding an objective response rate (ORR) of 60% and a disease control rate (DCR) of 100%, with the median progression-free survival (mPFS) not yet mature. Conclusions: Surufatinib combined with the EP regimen and serplulimab for NEC as first-line treatment showed notable efficacy and safety. The study established a phase II recommended surufatinib dose of 250mg, alongside immunotherapy and chemotherapy. Clinical trial information: NCT05747729 .
Prognostication of ß-catenin (CTNNB1) in patients with HCC treated with first line immunotherapy.
Authors: Shah Priyanshi M. , Peersen Anina , Jatoi Aminah , McWilliams Robert R. , Jin Zhaohui , Torbenson Michael S. , Halfdanarson Thorvardur Ragnar , Babiker Hani M. , Conboy Caitlin , Kankeu Fonkoua Lionel Aurelien , Washburn Leslie , Roberts Lewis R. , Gores Gregory J. , Bekaii-Saab Tanios S. , Borad Mitesh J. , Ou Fang-Shu , Tran Nguyen H.
Published: June 2024

e15146

Background: Wnt/ß-catenin signaling dysregulation is found in approximately 25% of hepatocellular carcinoma (HCC) patients. The impact of B-catenin activation on HCC overall survival has remained controversial. Prior studies suggest activating CTNNB1 mutations may predict for immunotherapy (IO) resistance while others did not corroborate this finding. Here we describe the clinical outcomes of advanced HCC patients (pts) with CTNNB1 (+) and without CTNNB1 (-) mutations treated with novel first line IO/anti-VEGF therapies. Methods: We conducted a multicenter, retrospective analysis of pts with HCC who had molecular analysis performed between 2019 and 2023 at Mayo Clinic in Minnesota, Arizona, and Florida. The study was reviewed and approved by the IRB. Clinical and molecular features were compared descriptively. The primary outcomes were time to treatment failure (TTF), defined as time from first-line treatment initiation to off treatment or death, and overall survival (OS), defined as time from first-line treatment initiation to death, compared between the two cohorts using the Kaplan-Meier method. Results: We identified 29 CTNNB1+ and 62 CTNNB1- (wt) pts with HCC. Median age at diagnosis was 66 (range 30-86), 80 (88%) were Caucasian, 68 (75%) were male gender, and 22 (24%) had etiology as hepatitis B/hepatitis C, 82 (90%) were Child-Pugh A and 77 (85%) were Barcelona Clinic Liver Clinic (BCLC)=C at diagnosis. Eighteen (90%, n=20) CTNNB 1+ pts received first-line IO (Atezolizumab/bevacizumab [AB]) vs 39 (72%, n=54) in CTNNB1- pts. All pts were microsatellite stable (MSS). CTNNB1+ had a similar median tumor mutational burden (TMB), higher rate of TERT co-mutation, and lower rate of TP53 co-mutation (table) compared to CTNNB-. Of 57 AB pts, 5 (27%) of CTNNB1 + had an objective response, compared to 6 (16.7%) CTNNB1- pts. Time to treatment failure with first-line AB and overall survival were similar between the two cohorts (Table). Conclusions: Our study suggests CTNNB1 status is not prognostic in HCC pts receiving IO based therapy. Prospective study is warranted to further investigate predictive biomarkers for HCC sensitivity to immune checkpoint inhibitors and VEGF-targeted therapy. [Table: see text]
A multi-modal artificial intelligence model trained on H&E tissue images and clinical patient data for prediction of BRAF mutations in colorectal cancer.
Authors: Paepper Marc , Frey Patrick , Mulder David , Daifalla Khalid , Faber Felix , Lang Tobias
Published: June 2024

e15161

Background: Analyzing genetic mutations is essential for personalized therapy decisions in oncology and beyond. In colorectal cancer (CRC), mutations in BRAF ( BRAFmut) render patients eligible for targeted treatment with BRAF inhibitors and immunotherapy. BRAFmut is routinely analyzed via genomic sequencing, which, however, is costly and does not provide diagnostic results immediately. Reliable detection of BRAFmut status from histological images using artificial intelligence (AI) could provide a more accessible and faster diagnostic alternative. Previous approaches to image-based BRAFmut analysis, however, failed to reach a critical level of accuracy on independent test cohorts, with reported area under the receiver operating characteristic curve (AUROC) values typically below 0.8. Methods: We hypothesized that combining tissue image analysis with clinical patient data could improve diagnostic accuracy for BRAFmut. Following our hypothesis, we developed a multi-modal AI model on n = 426 CRC cases from the TCGA database using BRAFmut data, H&E-stained tissue images, and information on patient parameters that are readily available in clinical practice and that are known to be associated with BRAFmut frequency. The model was based on a vision transformer architecture incorporating pathology-specific information using a pretrained embedding model for encoding tissue image features. Model performance was validated on an independent hold-out TCGA cohort of n = 107 samples and an additional external cohort of n = 104 CRC samples from the CPTAC database. Results: Our multi-modal AI model reached an AUROC of 0.85 ± 0.02 on the TCGA hold-out test set. Notably, on the second, external CPTAC dataset the predictive accuracy level was similar (AUROC of 0.83 ± 0.02) indicating the robustness of our approach to generalize to different datasets. Additional analyses showed that the significant performance boost over previous approaches was gained by the multi-modal analysis setup, as predicting BRAFmut based on either tissue, or clinical data alone led to lower accuracy values. Explainability analysis of AI results confirmed that relevant biological features on the histological slides, mainly tumor areas, were considered by the model for decision making. Conclusions: The combination of H&E images with clinically readily available patient parameters enabled us to develop a model predicting BRAFmut in CRC that surpasses previous approaches in diagnostic accuracy on independent evaluation cohorts. This indicates that combining histological tissue information with clinical parameters can increase the ability of AI models to predict genetic variants from tissue and more generally highlights the potential of multi-modal deep learning approaches to enhance predictive AI models in digital pathology.
NTRK positivity and conversion to appropriate personalized treatment.
Authors: Slifko Bethany Michelle , McLeod Howard L. , Moore Wendy , Abrunhosa Amaral Inês , Munksted Susanne
Published: June 2024

e15163

Background: The field of precision medicine continues to grow in size and complexity. In oncology alone, the FDA has approved companion diagnostics for 53 unique biomarkers across 28 different indications linking to 59 separate drugs to treat cancer patients beyond traditional options (FDA 21 December 2023). Two of these drugs, entrectinib and larotrectinib, are approved across all tumor types for NTRK fusions, which while rare in common cancer indications are more common in understudied, rare cancers (Cocco et al Nature 2018). These treatment options have significant outcomes for patients, however, there is still a large barrier for patients to access the right treatment (Sadik et al JCO 2022). We hypothesized not all patients with identified NTRK alterations are being prescribed these treatments and assessed this in real-world data for US oncology patients. Methods: Diaceutics proprietary DXRX database contains real-world claims, specialty pharmacy and laboratory data that enables the identification of patients positive for biomarker alterations and resultant treatment pathways in the US. The result-level laboratory data was filtered to solid tumor patients who were positive for NTRK alterations in the 2-year window between 2022 and 2023. The identified NTRK positive patients were then tokenized and joined to our medical claims and pharmacy data to assess which treatment combinations these patients received. Results: A total of 4,251 cancer patients were identified as having tumors with NTRK alterations. Of the patients that could be linked to treatment (800 patients), 1.5% (n = 12) patients went on to receive a targeted treatment for their NTRK alteration, either entrectinib (n = 8), larotrectinib (n = 3), or both entrectinib and larotrectinib (n = 1). When not prescribed either of these, 43.25% (n = 346) patients received different targeted treatment, possibly because of other alterations identified. There were still 55.25% (n = 442) receiving no targeted treatment, either being prescribed chemotherapy (chemo) alone (28.25%, n = 226), immunotherapy (IO) alone (21.1%, n = 169), or an IO/chemo combination (5.9%, n = 47). Conclusions: Despite the established significant disease control from targeted NTRK treatments, most patients with these alterationsdo not have an opportunity to benefit from the most effective personalized treatment for their cancer. These findings may suggest that targeted therapy for rarer and/or tissue agnostic alterations may get deprioritized or overlooked. Therefore, we advocate that a new, different approach for bringing targeted treatments for rare biomarkers to patients is still needed. Different economic models and an optimized approach to engage and inform key stakeholders including oncologists of the presence and benefit of targeted treatments is critical and needs further investigation.
Utilizing comprehensive next-generation sequencing to determine the clinical significance of copy number variation in advanced/metastatic non-small cell lung cancer.
Authors: EL Helali Aya , Ko Elaine Yee-Ling , Wong Charlene Hoi Lam , Shih David Jen-Hao , Wong Jason , Chiu Matthew , Lee Victor Ho-Fun
Published: June 2024

e15174

Background: Large population-based comprehensive tumor genomic profiling using next-generation sequencing (NGS) technology offers insight into the detection of copy number variation (CNV) in advanced/metastatic solid cancers. However, the significance and role of CNV in advanced-stage non-small cell lung cancer (NSCLC) is limited. In this analysis, we investigated the incidence and impact of CNV on patient outcomes. Methods: Patients were recruited as part of an ongoing real-world multicentre prospective NSCLC Precision Oncology Programme in Hong Kong. All patients underwent tissue and liquid NGS using Foundation One CDx and Foundation One Liquid CDx, respectively. Patients were classified into two groups based on CNV status: group 1 (CNV+) was defined as tumors with CNV reported; group 2 (CNV-) was defined as tumors with no CNV reported. The association of clinical factors with CNV was reported using Chi-square tests. The overall survival (OS) was calculated from the date of diagnosis of advanced-stage cancer to the date of death or the last follow-up date. Survival analysis was estimated using the Kaplan-Meier method with the log-rank test. Results: 353 patients were included in this analysis. NGS was performed in 216 (61%) tumor tissues, and 137 (39%) liquid specimens. 37% (n = 129) were female, and 50% (n = 175) were ever-smoker. 63% (n = 223) of our patient cohort harbored druggable mutations. The detection rate of CNV was 74% in tissue and 14% in liquid specimens. Patients with brain, liver, or bone metastasis (p = 0.018) and/or TMB-high (TMB-H) (p = 0.0014) were associated with CNV+. Next, we assessed the impact of CNV on treatment outcomes. Among patients who received immunotherapy ± chemotherapy, CNV+ was associated with a median OS of 20.4 months compared to 31.4 months in the CNV- group (HR:2.09, 95% CI: 1.05-4.16, p = 0.034). In contrast, there was no statistically significant difference in OS among the CNV+ and CNV- patient groups treated with chemotherapy alone. Although not significant, there was a trend towards poorer OS to immunotherapy ± chemotherapy in the TMB-H CNV+ cohort (23.6 months versus 31.4 months; p = 0.082). Conclusions: We demonstrate the significance of CNV as a prognostic tool for the prediction of survival outcomes among lung cancer patients. Our data suggests that CNV represents a distinct entity in advanced/metastatic NSCLC, associated with poorer survival outcomes to immunotherapy.
Reasons for biomarker testing in NSCLC: An analysis of reasoning between 2021-2023 in early- vs. late-stage patients.
Authors: Levent Ayse , De Richter Pieter
Published: June 2024

e15175

Background: Given the number of targeted therapies that are approved for non-small lung cancer (NSCLC), timely testing for biomarkers is critical to ensure eligible patients benefit from precision medicines. This study uses real-world data to explore how factors associated with routine and reflex testing in the US are influencing the decision to test for biomarkers. Methods: Ipsos’ MDx Monitor is a multi-stakeholder, physician-reported syndicated patient record database. Cancer-treating physicians in the US (2021 = 56, 2022 = 64, 2023 = 44) were screened for seniority and caseload and submitted data on 414 NSCLC patients (aggregate) who had been tested for biomarkers. Data were collected online in September-October of each year. Results: Comparing sampled physician-cited reasons for testing over time, standard procedure was mentioned more frequently in the reported 2023 cohort (87% in 2023 vs. 62% in 2021) as was lab performs this test as reflex (18% in 2023 vs. 2% in 2021). Testing because of patient histology or to inform treatment decision declined from 2021 to 2023. Reasons that were mentioned consistently more frequently among the reported early-stage patient cohorts vis-à-vis metastatic patients included histology, to inform treatment decision and, notably, patient request. The top cited reasons are shown in Table 1. Conclusions: Results from this study indicate that physicians’ approach to biomarker testing is evolving towards more routine procedures, rather than testing to inform a specific treatment decision, marked by a recorded increase in reflex and broader panel-based testing. Although guidelines focus on assessing metastatic patients’ eligibility for targeted therapies, early-stage patients also stand to benefit from more automated testing processes. Further investigation on time between diagnosis and implementation of biomarker testing, along with subsequent treatment outcomes, is warranted. [Table: see text]
INSIHGT: A scalable and homogeneous 3D multiplexed molecular mapping platform for spatial biology and precision medicine.
Authors: Lai Hei Ming , Chow King Ngai , Hung Tin Shing , Yau Chun Ngo , Chan Shuk Ling
Published: June 2024

e15180

Background: The dynamic interplay between cancer cells and their microenvironment is a determinant of disease evolution and response to treatment. However, the current state of three-dimensional (3D) tumor microenvironment analysis is hindered by inadequate penetration of antibodies into thick tissue sections, leading to a substantial gap in acquiring unbiased, precise 3D multiplexed immunohistochemistry (IHC) images. Methods: We developed INSIHGT to surmount these limitations by enabling multi-round, multiplexed 3D IHC in standard formalin-fixed tissues. This fully automatable, fast-track method requires a simple series of chemical cocktail exchanges, translating to a tissue-to-image time of 6 days for 1 cm³ samples and as little as 6 hours for biopsy specimens. INSIHGT offers a scalable and efficient solution for detailed 3D spatial mapping of cancerous cells and their interactions within their native context. Results: 3D IHC with INSIHGT shows ideal penetration homogeneity, which quantitatively matches reference signals in 1cm3 samples. We further validated INSIHGT with 309 commercially available primary antibodies and is compatible with simultaneous fluorescent in situ hybridization (FISH) to detect RNA transcripts or DNA chromosomal abnormalities. Notably, the quality of post-INSIHGT traditional histological analyses, such as H&E and standard IHC, was not altered. We demonstrated a 3D mapping of over 20 markers in a 1 mm-thick tumor sample across seven INSIHGT cycles, and an atlas of multiple tumour samples with 3D IHC & H&E. The large datasets seamlessly integrates with single-cell segmentation and analysis workflows, yielding comprehensive maps that elucidate protein expression, cell morphology, spatial positioning, and potential cell-cell interactions. Conclusions: INSIHGT provides an unparalleled level of visualization and analytical detail concerning the spatial dynamics within the tumor microenvironment at a single-cell resolution. As a transformative next generation histopathology platform, it can uncover new structural and molecular details within clinical specimens, accelerating biomarker discovery and novel diagnostic assays development, thereby enriching the field of tumor biology and propelling the progress of personalized oncology treatments.
Using sample reinterrogation to guide high-parameter, spatially resolved tissue biomarker discovery.
Authors: Schwarz J. Spencer , Berigan Benton , Ingalls Matthew , Meshik Xenia , Jackson Charles , Cashion Kayla , Christians Arne , Brix Anke , Boettcher Marcus , Braubach Oliver
Published: June 2024

e15182

Background: High-parameter, spatially resolved phenotyping can accelerate the discovery of tissue biomarkers as well as reveal emergent disease indicators like cellular neighborhood architecture. These spatial biology techniques hold high potential as diagnostic and prognostic indicators yet can be challenging to deploy due to high cost and lack of standardization. We have developed a powerful spatial biology workflow based on multiplex cyclic immunofluorescent (IF) staining using validated markers and assay kits that allows the researcher to adjust the markers included in the assay with feedback from marker expression in previous rounds. We term this sample re-interrogation. Here we present an illustration of this new workflow. Methods: Three FFPE lung biopsy specimens were repeatedly assayed for biomarker expression using CellScape™ Precise Spatial Multiplexing paired with VistaPlex™ Assay Kits. In this workflow, tissues are mounted in enclosed fluidic chambers. IF Staining and imaging were conducted on the CellScape instrument as iterative rounds. Between each imaging round, we conducted analyses on data from previously collected rounds. Conclusions drawn between staining rounds then guided decisions of whether and how to continue the experiment. Results: Each sample provided evidence for the utility of staged rounds of tissue staining, analysis, and rational assay planning. Two FFPE lung samples from the biopsy were not considered for further iterative staining after initial interrogation for consensus markers resulted in poor expression ( e.g.: CD4, CD20, CD45, pan-cytokeratin). One of these two samples was stained with markers indicative of cell death pathways and fibrosis to provide a positive explanation for initial poor staining. A third lung tissue showed punitive indication of tertiary lymphoid structure (TLS) inclusion. Further rounds of staining were conducted to iteratively explore the nature of these punitive TLS structures. Each round of additional stains was chosen based on data derived from the previous staining series following analysis and deliberation among the biomarker team. Conclusions: The data illustrate that even among tissue sections taken from the same biopsy, a specimen’s unique biomarker expression profile may require adjustments to assay parameters. Two of the FFPE sections proved unacceptable for further investigation after only a handful of stains. This finding highlights the benefit of rational reinterrogation, as the saved resources in not staining these tissues could measure in the thousands of dollars in reagents alone. The third lung tissue specimen offers an example of a tailored spatial biology assay through iterative reinterrogation. All included biomarkers were judged best suited to elucidate the next round of staining, representing an optimized and flexible spatial biology workflow.
Relevance of immune tumor microenvironment and its interaction with HABP4 and SERBP1 proteins in bladder cancer.
Authors: Fávaro Wagner José , Camargo Gabriela Cardoso de Arruda , Oliveira Gabriela , Roberto Isadora Manzato , Ávila Monaliza , Santos André Da Silva , Freitas Leandro Luiz Lopes de , Billis Athanase , Alonso João Carlos Cardoso
Published: June 2024

e15187

Background: This study characterized and compared the immunohistochemical signatures associated with the cytotoxic inflammatory response (IFN-γ, CX3CR1+CD8+ T cells, iNOS+ M1 macrophages), immune checkpoints (PD-L1, CTLA-4), and the presence of immunosuppressive cells (CD163+M2 macrophages, Foxp3+regulatory T (Treg) cells) within bladder cancer samples. Furthermore, it aimed to correlate these immune signatures with the functional dynamics of Hyaluronic Acid Binding Protein 4 (HABP4) and Serpin mRNA Binding Protein 1 (SERBP1), proposing a novel perspective on the immunobiology of bladder cancer and its implications for targeted therapeutic strategies. Methods: A total of 30 formalin-fixed, paraffin-embedded bladder samples were obtained from patients aged 34 to 96 years (average 65 years) diagnosed with bladder cancer at the Municipal Hospital of Paulínia, Brazil. The samples were divided into three groups (n = 10 samples per group): Group 1 - Initial Non-Muscle Invasive Bladder Cancer (NMIBC); Group 2 - Bacillus Calmette-Guerin (BCG)-unresponsive NMIBC; and Group 3 - Muscle Invasive Bladder Cancer. Subsequently, the samples were submitted to immunohistochemical analyses. The retrospective anonymous study was approved by the local ethics committee (Clinical Trial: RBR-6swqd2). Results: Our results demonstrated that total immunoreactivities for IFN-γ, iNOS and CX3CR1 were significantly higher (p < 0.01) in Group 1 compared to Groups 2 and 3. CTLA-4 and PD-L1 immunoreactivities were significantly higher (p < 0.01) in Group 1 compared to Groups 2 and 3. Conversely, immunoreactivities for CD163 and Foxp3 were significantly higher (p < 0.01) in Groups 2 and 3 compared to Group 1. This study marks the first elucidation of HABP4 and SERBP1 immunoreactivities in the context of bladder cancer. We observed that immunoreactivity for SERBP1 was significantly higher (p < 0.01) in Groups 2 and 3 than in Group 1, implicating its overexpression in the facilitation of tumor progression. In a contrasting manner, HABP4 demonstrated significantly greater immunoreactivity (p < 0.01) in Group 1 compared to Groups 2 and 3, indicating a potential inhibitory effect on cellular proliferation. Conclusions: The augmented presence of Foxp3+Treg cells and CD163+M2 macrophages, concomitant with SERBP1 overexpression and the decrease of immune checkpoints, likely compromises the therapeutic efficacy of BCG. This immunosuppressive milieu hinders the activation, proliferation, and effector functions of CD8+ T cells, thereby promoting tumor progression. Conversely, a heightened infiltration of CX3CR1+CD8+ T cells and iNOS+M1 macrophages promotes a cytotoxic microenvironment, rendering it more amenable to immunotherapeutic interventions.
AURKA blockage as a strategy to overcome resistance to olaparib and platinum in high-grade ovarian cancer (HGOC).
Authors: Martínez-Pretel Juan José , Heredia Victoria , Ruiz Linuesa Miriam , Sanchez Serrano Paloma , Gonzalez Villena Lidia , Mendiola Marta , Redondo Andres , Pineda Begoña , Perez-Fidalgo Jose Alejandro
Published: June 2024

e15198

Background: PARP inhibitors (PARPi) as olaparib (OLA) have become the new standard in maintenance treatment in high grade ovarian carcinoma (HGOC). Thus, there is an important need to identify the mechanisms for PARPi resistance and the strategies to overcome them. Our aim is to assess if in vitro inhibition of AURKA, a protein that plays a relevant role in centrosome spindle formation and mitotic regulation, might overcome olaparib resistance mechanisms in HGOC. Methods: Three HGOC cell lines (PEO1, Kuramochi and SKOV3) were selected, and isogenic resistant pairs generated in vitro, by pulsed exposure to OLA (PEO1-R) or by exposure to growing concentrations of OLA (Kuramochi-R and SKOV-R). AURKA expression was assessed by PCR and Western blot (WB). Cells were OLA-treated before and after the downregulation of AURKA expression by a specific small inhibitor RNA (siRNA) and by pharmacologic inhibition with alisertib. Cell viability was assessed by MTT assay and DNA damage by the evaluation of markers by WB. Combination index of the combo OLA+alisertib was assessed by Chou-Talalay method. Results: AURKA expression was lower at gene and protein levels in resistant cell lines compared to parental. Upon AURKA silencing (Si) of parental (OLA-sensitive) cell lines, no differences in the OLA IC50 values between AURKA-Si and control cells were seen. However AURKA-Si of the OLA-resistant cell lines was associated with a decreased in OLA IC50 as follows: 1) In PEO1R control scramble siRNA (sc) was 226 mM vs SI 128 mM, p < 0.0001; 2) In Kuramochi-R scRNA 268.4 mM vs si 130.2 mM p < 0.0001 and 3) in SKOV3-R scRNA 187 mM vs si 74.7 mM, p < 0.0001 suggesting a role of AURKA-si in overcoming OLA-resistance. Pharmacologic AURKA targeting with the inhibitor alisertib in all 3 sensitive and resistant cell lines showed an increase of DNA damage measured by the expression of H2AX protein by WB. Combination index of the OLA+alisertib in all resistant cell lines showed a synergistic effect of the combination with PEO1-R FA50 = 0.25 (FA25-75 0.2-0.31), Kuramochi-R FA50 = 0.29 (0.19-9.36) and SKOV3-R FA50 = 0.24 (0.19-0.36). Conclusions: AURKA targeting either by silencing or pharmacologic inhibition increased OLA-induced apoptosis or had a synergistic effect in OLA-resistant cell lines suggesting AURKA as a potential target for overcoming OLA resistance.
Exploring CK2 transcriptional regulation and signaling pathways in cancer.
Authors: Wilson Nicholas , Figueroa Cristián , Kreber Isabelle , Dominguez Isabel M.
Published: June 2024

e15199

Background: CK2 genes have been implicated in oncogenic processes in different cancer types, and their expression is known to be increased in many cancers relative to their normal tissue types. However the regulation of the three CK2 alpha transcripts and beta transcript is not well understood. Studies investigating the alpha gene ( CSNK2A1) and beta gene ( CSNK2B) found NFκB, ETS1, and SP1 as likely transcription factor regulators in lymphoid and fibroblast cell lines. Our study seeks to explore correlations between CK2 gene expression and the expression of these transcription factors in cancer. Since CK2 also regulates intracellular signaling through pathways such as PI3K-Akt, Jak-Stat, NFkB, Wnt, IL-6, TGF-β, Ras and Notch, this study also seeks to explore the correlation between CK2 expression and gene expression of known downstream signaling pathways across a variety of cancers. Methods: 32 non-overlapping cancer datasets were obtained from the The Cancer Genome Atlas (TCGA) and Broad GDAC Firehose projects which were obtained via cBioPortal.org and analyzed using a combination of cBioportal and RStudio statistical analysis packages. For each cancer type, mRNA expression of each of the four CK2 genes in cancer was compared to expression of transcription factors both previously identified in the literature and predicted generated by TFBIND analysis (via the transcription factor database TRANSFAC R3.4) of the CK2 minimal promoter regions. CK2 gene expression was also compared to expression of genes in known CK2 signaling pathways. Results: Our analysis found CSNK2A1 and CSNK2A3 expression to have a significant, strong positive correlation in nearly all cancer types studied, except pancreatic adenocarcinoma. CSNK2A1 demonstrated significant positive correlation with expression of the transcription factors NFKB1 and c-Rel in lymphoma, thymoma, and other cancers. CSNK2B demonstrated a significant, strong positive correlation with the transcription factors NELFE in every cancer examined. CK2 transcripts also showed significant correlations with other transcription factors and genes involved in IL-6, TGF-β, MAPK, and several other CK2 signaling pathways in many different cancer types. Conclusions: Overall this study demonstrates significant correlations between CK2 gene expression and previously proposed transcriptional regulation mechanisms as well as known CK2 signaling pathways in cancer.
A new prognostic tool for metastatic colorectal cancer patients receiving anti-angiogenic treatment, the PALM score: A single-center experience.
Authors: Lai Eleonora , Palmas Enrico , Loi Francesco , Ziranu Pina , Mariani Stefano , Pretta Andrea , D'Agata Alessandra Pia , Dell'Utri Veronica , Papalexis Giulia , Deias Giulia , Rizzo Daiana , Spanu Dario , Sanna Giorgia , Moledda Giusy , Cadoni Andrea , Cucca Mattia , Donisi Clelia , Pusceddu Valeria , Puzzoni Marco , Scartozzi Mario
Published: June 2024

e15575

Background: Even if anti-angiogenic agents are crucial for metastatic colorectal cancer (mCRC) patients (pts) treatment, to date, no validated prognostic biomarkers are available. We conducted at our Centre a retrospective research to identify a prognostic tool to be applied in clinical practice in this population. Methods: We retrospectively collected laboratory, radiological and clinical data of mCRC pts treated with anti-angiogenic agents at the Medical Oncology Unit of Cagliari University Hospital (2018- 02/2024) in order to identify a potential prognostic tool. Statistical analysis was performed with MedCalc (survival distribution: Kaplan-Meier; survival comparison: log-rank test; cut-off: ROC curves; differences among variables: Chi-square test). Results: Globally, 33 mCRC pts were evaluated in our study (19 male, 14 female; 13 RAS wild-type, 22 left-sided primary). 10 were treated with anti-angiogenic drugs in the 1st-line, 13 in the 2nd-line (bevacizumab and aflibercept) and 10 in 1st-2nd line. Median OS was 39.5 months (m) (95%CI:28.2-41.3), median Progression Free Survival (PFS) was 14.9 m (95%CI:9.5-18.5). Pts with lower platelet to lymphocyte ratio (P; ≤253; p < 0.0001, HR = 0,00000048; 95%CI 24.7-39.5 versus [vs] 95% CI 8.2-10.5), alkaline phosphatase (A; < 136 U/l; p = 0.0001, HR = 0.0001; 95%CI 12-39.5 vs 95% CI 8.2-10.5) and lactate dehydrogenasis (L; < 365 U/l; p < 0.0001, HR = 0.0000004; 95%CI 24.7-39.5 vs 95% CI 8.2-10.5) and higher monocyte count (M; > 0.3x103/μL; p = 0.0093, HR 0.01; 95%CI 26.5-39.5 vs 95%CI 8.2-24.7), showed a statistically improved OS. We created the “PALM score” and separated pts in two prognostic groups: good prognostic group (0 unfavorable variables: PALM = 0) and poor prognostic group (≥1 unfavorable variable, PALM = 1). OS was significantly improved in the good prognostic group (PALM = 0): 31.5 m (95%CI:24.7-39.5) vs 10.5 m (PALM = 1) (p = 0.0031, HR = 0.00006). Chi-square test revealed also a statistically significant correlation of upfront resection of primary tumor with the PALM score (73.9% of patients belonging to the PALM = 0 group had undergone surgery for primary tumor and all patients with resected primary belonged to the PALM = 0 group (p = 0.0352). Conclusions: Our research showed a promising prognostic role of easy-to-use PALM score tool in mCRC patients treated with anti-angiogenic drugs in a limited population at our center. Further prospective studies with larger sample size are needed to confirm our findings.