The molecular signature and prognosis of glioma with preoperative intratumoral hemorrhage: a retrospective cohort analysis.

BACKGROUND: Intratumoral hemorrhage, though less common, could be the first clinical manifestation of glioma and is detectable via MRI; however, its exact impacts on patient outcomes remain unclear and controversial. The 2021 WHO CNS 5 classification emphasised genetic and molecular features, initiating the necessity to establish the correlation between hemorrhage and molecular alterations. This study aims to determine the prevalence of intratumoral hemorrhage in glioma subtypes and identify associated molecular and clinical characteristics to improve patient management. METHODS: Integrated clinical data and imaging studies of patients who underwent surgery at the Department of Neurosurgery at Peking Union Medical College Hospital from January 2011 to January 2022 with pathological confirmation of glioma were retrospectively reviewed. Patients were divided into hemorrhage and non-hemorrhage groups based on preoperative magnetic resonance imaging. A comparison and survival analysis were conducted with the two groups. In terms of subgroup analysis, we classified patients into astrocytoma, IDH-mutant; oligodendroglioma, IDH-mutant, 1p/19q-codeleted; glioblastoma, IDH-wildtype; pediatric-type gliomas; or circumscribed glioma using integrated histological and molecular characteristics, according to WHO CNS 5 classifications. RESULTS: 457 patients were enrolled in the analysis, including 67 (14.7%) patients with intratumoral hemorrhage. The hemorrhage group was significantly older and had worse preoperative Karnofsky performance scores. The hemorrhage group had a higher occurrence of neurological impairment and a higher Ki-67 index. Molecular analysis indicated that CDKN2B, KMT5B, and PIK3CA alteration occurred more in the hemorrhage group (CDKN2B, 84.4% vs. 62.2%, p = 0.029; KMT5B, 25.0% vs. 8.9%, p = 0.029; and PIK3CA, 81.3% vs. 58.5%, p = 0.029). Survival analysis showed significantly worse prognoses for the hemorrhage group (hemorrhage 18.4 months vs. non-hemorrhage 39.1 months, p = 0.01). In subgroup analysis, the multivariate analysis showed that intra-tumoral hemorrhage is an independent risk factor only in glioblastoma, IDH-wildtype (162 cases of 457 overall, HR = 1.72, p = 0.026), but not in other types of gliomas. The molecular alteration of CDK6 (hemorrhage group p = 0.004, non-hemorrhage group p < 0.001), EGFR (hemorrhage group p = 0.003, non-hemorrhage group p = 0.001), and FGFR2 (hemorrhage group p = 0.007, non-hemorrhage group p = 0.001) was associated with shorter overall survival time in both hemorrhage and non-hemorrhage groups. CONCLUSIONS: Glioma patients with preoperative intratumoral hemorrhage had unfavorable prognoses compared to their nonhemorrhage counterparts. CDKN2B, KMT5B, and PIK3CA alterations were associated with an increased occurrence of intratumoral hemorrhage, which might be future targets for further investigation of intratumoral hemorrhage.

Exploring the biology of ctDNA release in colorectal cancer.

BACKGROUND: Circulating tumor DNA (ctDNA) has emerged as a promising tool for early cancer detection and minimal residual disease monitoring. However, the biology underlying ctDNA release and its variation across cancer types and histologies remains poorly understood. This study investigated the biology behind ctDNA shedding in colorectal cancer. METHODS: The study included a local cohort of 747 stage I-III colorectal cancer patients. All patients had ctDNA measurement prior to treatment and extensive clinical data. Primary tumor RNA sequencing and whole exome sequencing was performed in 95 and 652 patients respectively. Additionally, the study evaluated 89 non-small cell lung cancer patients from the TRACERx cohort, comprising primary tumor RNA sequencing and ctDNA measurement. RESULTS: We found tumor size and proliferative capacity to be key factors associated with ctDNA shedding in colorectal cancer. Furthermore, we found that the secretory and CMS3 colorectal cancer subtypes exhibited lower ctDNA shedding, while microsatellite instability (MSI) tumors had higher levels of ctDNA. Mutational analysis did not reveal any genes or pathways associated with ctDNA shedding in colorectal cancer. A comparison of transcriptomic profiles across multiple cancer types demonstrated that colorectal cancer and lung squamous cell carcinoma tumors shared a high-proliferative ctDNA shedding phenotype, while lung adenocarcinoma tumors displayed a distinct low-proliferative subgroup. Additionally, proliferation levels correlated with ctDNA detection sensitivity across multiple cancer types. CONCLUSION: These findings suggest that tumor size and proliferative capacity are drivers of ctDNA release in colorectal cancer and provide insights into the biology of ctDNA shedding on a pan-cancer level.

Pyroptosis activates conventional type I dendritic cells to mediate the priming of highly functional anticancer T cells.

BACKGROUND: Initiation of antitumor immunity is reliant on the stimulation of dendritic cells (DCs) to present tumor antigens to naïve T cells and generate effector T cells that can kill cancer cells. Induction of immunogenic cell death after certain types of cytotoxic anticancer therapies can stimulate T cell-mediated immunity. However, cytotoxic therapies simultaneously activate multiple types of cellular stress and programmed cell death; hence, it remains unknown what types of cancer cell death confer superior antitumor immunity. METHODS: Murine cancer cells were engineered to activate apoptotic or pyroptotic cell death after Dox-induced expression of procell death proteins. Cell-free supernatants were collected to measure secreted danger signals, cytokines, and chemokines. Tumors were formed by transplanting engineered tumor cells to specifically activate apoptosis or pyroptosis in established tumors and the magnitude of immune response measured by flow cytometry. Tumor growth was measured using calipers to estimate end point tumor volumes for Kaplan-Meier survival analysis. RESULTS: We demonstrated that, unlike apoptosis, pyroptosis induces an immunostimulatory secretome signature. In established tumors pyroptosis preferentially activated CD103+ and XCR1+ type I conventional DCs (cDC1) along with a higher magnitude and functionality of tumor-specific CD8+ T cells and reduced number of regulatory T cells within the tumor. Depletion of cDC1 or CD4+ and CD8+ T cells ablated the antitumor response leaving mice susceptible to a tumor rechallenge. CONCLUSION: Our study highlights that distinct types of cell death yield varying immunotherapeutic effect and selective activation of pyroptosis can be used to potentiate multiple aspects of the anticancer immunity cycle.

The effectiveness of CA125 and HE4 as clinical prognostic markers in epithelial ovarian cancer patients with BRCA mutation.

OBJECTIVE: To investigate the efficacy of cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) in predicting survival outcomes based on breast cancer gene (BRCA) mutational status in epithelial ovarian cancer. METHODS: Medical records of 448 patients diagnosed with epithelial ovarian cancer at a single tertiary institution in Korea were retrospectively analyzed. Area under the curve, sensitivity, specificity, and accuracy were assessed using the CA125 and HE4 values after surgery and 3 cycles of chemotherapy to predict 1-year survival based on the BRCA mutational status. Kaplan-Meier analysis was used to obtain progression-free and overall survival to evaluate CA125 and HE4 effectiveness in predicting survival outcomes. RESULTS: A total of 423 patients were analyzed, including 180 (42.6%) who underwent interval debulking surgery (IDS) and 243 (57.4%) who underwent primary debulking surgery (PDS). BRCA mutations were observed in 37 (15.2%) and 44 (22.4%) patients in the PDS and IDS groups, respectively. CA125 and HE4 normalization demonstrated the highest specificity in patients with or without BRCA mutations, with specificities of 97.1% and 99.1% in the PDS group and 78.6% and 86.2% in the IDS group, respectively. Normalizing HE4 alone may be an effective prognostic marker, with an area under the curve of 0.774 and specificity of 75.0%, in patients with BRCA mutations. CONCLUSION: Normalizing both biomarkers emerged as the most effective predictive marker for the 1-year recurrence rate, regardless of BRCA mutational status. A negative HE4 value can be a useful predictor for 1-year recurrence-free survival in patients with BRCA mutations.

Clinicopathological Features and Molecular Signatures of Lateral Neck Lymph Node Metastasis in Papillary Thyroid Microcarcinoma.

BACKGRUOUND: The predictive factors for lateral neck lymph node metastasis (LLNM) in papillary thyroid microcarcinoma (PTMC) remain undetermined. This study investigated the clinicopathological characteristics, transcriptomes, and tumor microenvironment in PTMC according to the LLNM status. We aimed to identify the biomarkers associated with LLNM development. METHODS: We retrospectively reviewed the medical records of patients with PTMC from two independent institutions between 2018 and 2022 (n=597 and n=467). We compared clinicopathological features between patients without lymph node metastasis (N0) and those with LLNM (N1b). Additionally, laser capture microdissection and RNA sequencing were performed on primary tumors from both groups, including metastatic lymph nodes from the N1b group (n=30; 20 primary tumors and 10 paired LLNMs). We corroborated the findings using RNA sequencing data from 16 BRAF-like PTMCs from The Cancer Genome Atlas. Transcriptomic analyses were validated by immunohistochemical staining. RESULTS: Clinicopathological characteristics, such as male sex, multifocality, extrathyroidal extension, lymphatic invasion, and central node metastasis showed associations with LLNM in PTMCs. Transcriptomic profiles between the N0 and N1b PTMC groups were similar. However, tumor microenvironment deconvolution from RNA sequencing and immunohistochemistry revealed an increased abundance of tumor-associated macrophages, particularly M2 macrophages, in the N1b group. CONCLUSION: Patients with PTMC who have a male sex, multifocality, extrathyroidal extension, lymphatic invasion, and central node metastasis exhibited an elevated risk for LLNM. Furthermore, infiltration of M2 macrophages in the tumor microenvironment potentially supports tumor progression and LLNM in PTMCs.

Total metabolic tumor volume on 18F-FDG PET/CT is a game-changer for patients with metastatic lung cancer treated with immunotherapy.

PURPOSE: Because of atypical response imaging patterns in patients with metastatic non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICPIs), new biomarkers are needed for a better monitoring of treatment efficacy. The aim of this prospective study was to evaluate the prognostic value of volume-derived positron-emission tomography (PET) parameters on baseline and follow-up 18F-fluoro-deoxy-glucose PET (18F-FDG-PET) scans and compare it with the conventional PET Response Criteria in Solid Tumors (PERCIST). METHODS: Patients with metastatic NSCLC were included in two different single-center prospective trials. 18F-FDG-PET studies were performed before the start of immunotherapy (PETbaseline), after 6-8 weeks (PETinterim1) and after 12-16 weeks (PETinterim2) of treatment, using PERCIST criteria for tumor response assessment. Different metabolic parameters were evaluated: absolute values of maximum standardized uptake value (SUVmax) of the most intense lesion, total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), but also their percentage changes between PET studies (ΔSUVmax, ΔTMTV and ΔTLG). The median follow-up of patients was 31 (7.3-31.8) months. Prognostic values and optimal thresholds of PET parameters were estimated by ROC (Receiver Operating Characteristic) curve analysis of 12-month overall survival (12M-OS) and 6-month progression-free survival (6M-PFS). Tumor progression needed to be confirmed by a multidisciplinary tumor board, considering atypical response patterns on imaging. RESULTS: 110 patients were prospectively included. On PETbaseline, TMTV was predictive of 12M-OS [AUC (Area Under Curve) =0.64; 95% CI: 0.61 to 0.66] whereas SUVmax and TLG were not. On PETinterim1 and PETinterim2, all metabolic parameters were predictive for 12M-OS and 6M-PFS, the residual TMTV on PETinterim1 (TMTV1) being the strongest prognostic biomarker (AUC=0.83 and 0.82; 95% CI: 0.74 to 0.91, for 12M-OS and 6M-PFS, respectively). Using the optimal threshold by ROC curve to classify patients into three TMTV1 subgroups (0 cm3; 0-57 cm3; >57 cm3), TMTV1 prognostic stratification was independent of PERCIST criteria on both PFS and OS, and significantly outperformed them. Subgroup analysis demonstrated that TMTV1 remained a strong prognostic biomarker of 12M-OS for non-responding patients (p=0.0003) according to PERCIST criteria. In the specific group of patients with PERCIST progression on PETinterim1, low residual tumor volume (<57 cm3) was still associated with a very favorable patients' outcome (6M-PFS=73%; 24M-OS=55%). CONCLUSION: The absolute value of residual metabolic tumor volume, assessed 6-8 weeks after the start of ICPI, is an optimal and independent prognostic measure, exceeding and complementing conventional PERCIST criteria. Oncologists should consider it in patients with first tumor progression according to PERCIST criteria, as it helps identify patients who benefit from continued treatment. TRIAL REGISTRATION NUMBER: 2018-A02116-49; NCT03584334.

Association of metabolomics with PD-1 inhibitor plus chemotherapy outcomes in patients with advanced non-small-cell lung cancer.

BACKGROUND: Combining immune checkpoint inhibitors (ICIs) with chemotherapy has become a standard treatment for patients with non-small cell lung cancer (NSCLC) lacking driver gene mutations. Reliable biomarkers are essential for predicting treatment outcomes. Emerging evidence from various cancers suggests that early assessment of serum metabolites could serve as valuable biomarkers for predicting outcomes. This study aims to identify metabolites linked to treatment outcomes in patients with advanced NSCLC undergoing first-line or second-line therapy with programmed cell death 1 (PD-1) inhibitors plus chemotherapy. METHOD: 200 patients with advanced NSCLC receiving either first-line or second-line PD-1 inhibitor plus chemotherapy, and 50 patients undergoing first-line chemotherapy were enrolled in this study. The 200 patients receiving combination therapy were divided into a Discovery set (n=50) and a Validation set (n=150). These sets were further categorized into respond and non-respond groups based on progression-free survival PFS criteria (PFS≥12 and PFS<12 months). Serum samples were collected from all patients before treatment initiation for untargeted metabolomics analysis, with the goal of identifying and validating biomarkers that can predict the efficacy of immunotherapy plus chemotherapy. Additionally, the validated metabolites were grouped into high and low categories based on their medians, and their relationship with PFS was analyzed using Cox regression models in patients receiving combination therapy. RESULTS: After the impact of chemotherapy was accounted for, two significant differential metabolites were identified in both the Discovery and Validation sets: N-(3-Indolylacetyl)-L-alanine and methomyl (VIP>1 and p<0.05). Notably, upregulation of both metabolites was observed in the group with a poorer prognosis. In the univariate analysis of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were associated with longer PFS (HR=0.59, 95% CI, 0.41 to 0.84, p=0.003), and a prolonged PFS was also indicated by lower levels of methomyl (HR=0.67, 95% CI, 0.47 to 0.96, p=0.029). In multivariate analyses of PFS, lower levels of N-(3-Indolylacetyl)-L-alanine were significantly associated with a longer PFS (HR=0.60, 95% CI, 0.37 to 0.98, p=0.041). CONCLUSION: Improved outcomes were associated with lower levels of N-(3-Indolylacetyl)-L-alanine in patients with stage IIIB-IV NSCLC lacking driver gene mutations, who underwent first-line or second-line therapy with PD-1 inhibitors combined with chemotherapy. Further exploration of the potential predictive value of pretreatment detection of N-(3-Indolylacetyl)-L-alanine in peripheral blood for the efficacy of combination therapy is warranted. STATEMENT: The combination of ICIs and chemotherapy has established itself as the new standard of care for first-line or second-line treatment in patients with advanced NSCLC lacking oncogenic driver alterations. Therefore, identifying biomarkers that can predict the efficacy and prognosis of immunotherapy plus chemotherapy is of paramount importance. Currently, the only validated predictive biomarker is programmed cell death ligand-1 (PD-L1), but its predictive value is not absolute. Our study suggests that the detection of N-(3-Indolylacetyl)-L-alanine in patient serum with untargeted metabolomics prior to combined therapy may predict the efficacy of treatment. Compared with detecting PD-L1 expression, the advantage of our biomarker is that it is more convenient, more dynamic, and seems to work synergistically with PD-L1 expression.

Molecular assessment of intratumoral immune cell subsets and potential mechanisms of resistance to odronextamab, a CD20×CD3 bispecific antibody, in patients with relapsed/refractory B-cell non-Hodgkin lymphoma.

BACKGROUND: Patients with relapsed/refractory B-cell non-Hodgkin lymphoma (R/R B-NHL) have a significant need for effective treatment options. Odronextamab is an Fc-silenced, human, CD20×CD3 bispecific antibody that targets CD20-expressing cells via T-cell-mediated cytotoxicity independent of T-cell/major histocompatibility complex interaction. Phase I results in patients with R/R B-NHL demonstrated that odronextamab monotherapy could achieve deep and durable responses with a generally manageable safety profile (ELM-1; NCT02290951). As part of a biomarker analysis of the same study, we investigated potential biomarkers and mechanisms of resistance to odronextamab. METHODS: Patients with R/R B-NHL enrolled in ELM-1 received one time per week doses of intravenous odronextamab for 4×21 day cycles, then doses every 2 weeks thereafter. Patient tumor biopsies were obtained at baseline, on-treatment, and at progression. Immune cell markers were analyzed by immunohistochemistry, flow cytometry, single-cell RNA sequencing, and whole genome sequencing. RESULTS: Baseline tumor biopsies showed that almost all patients had high proportions of B cells that expressed the CD20 target antigen, whereas expression of other B-cell surface antigens (CD19, CD22, CD79b) was more variable. Responses to odronextamab in patients with diffuse large B-cell lymphoma were not related to the relative level of baseline CD20 expression, cell of origin, or high-risk molecular subtype. A potential link was observed between greater tumor programmed cell death-ligand 1 expression and increased likelihood of response to odronextamab. Similarly, a trend was observed between clinical response and increased levels of CD8 T cells and regulatory T cells at baseline. We also identified an on-treatment pharmacodynamic shift in intratumoral immune cell subsets. Finally, loss of CD20 expression through inactivating gene mutations was identified as a potential mechanism of resistance in patients who were treated with odronextamab until progression, as highlighted in two detailed patient cases reported here. CONCLUSIONS: This biomarker analysis expands on clinical findings of odronextamab in patients with R/R B-NHL, providing verification of the suitability of CD20 as a therapeutic target, as well as evidence for potential mechanisms of action and resistance.

Repeatability of deuterium metabolic imaging of healthy volunteers at 3 T.

BACKGROUND: Magnetic resonance (MR) imaging of deuterated glucose, termed deuterium metabolic imaging (DMI), is emerging as a biomarker of pathway-specific glucose metabolism in tumors. DMI is being studied as a useful marker of treatment response in a scan-rescan scenario. This study aims to evaluate the repeatability of brain DMI. METHODS: A repeatability study was performed in healthy volunteers from December 2022 to March 2023. The participants consumed 75 g of [6,6'-2H2]glucose. The delivery of 2H-glucose to the brain and its conversion to 2H-glutamine + glutamate, 2H-lactate, and 2H-water DMI was imaged at baseline and at 30, 70, and 120 min. DMI was performed using MR spectroscopic imaging on a 3-T system equipped with a 1H/2H-tuned head coil. Coefficients of variation (CoV) were computed for estimation of repeatability and between-subject variability. In a set of exploratory analyses, the variability effects of region, processing, and normalization were estimated. RESULTS: Six male participants were recruited, aged 34 ± 6.5 years (mean ± standard deviation). There was 42 ± 2.7 days between sessions. Whole-brain levels of glutamine + glutamate, lactate, and glucose increased to 3.22 ± 0.4 mM, 1.55 ± 0.3 mM, and 3 ± 0.7 mM, respectively. The best signal-to-noise ratio and repeatability was obtained at the 120-min timepoint. Here, the within-subject whole-brain CoVs were -10% for all metabolites, while the between-subject CoVs were -20%. CONCLUSIONS: DMI of glucose and its downstream metabolites is feasible and repeatable on a clinical 3 T system. TRIAL REGISTRATION: ClinicalTrials.gov, NCT05402566 , registered the 25th of May 2022. RELEVANCE STATEMENT: Brain deuterium metabolic imaging of healthy volunteers is repeatable and feasible at clinical field strengths, enabling the study of shifts in tumor metabolism associated with treatment response. KEY POINTS: • Deuterium metabolic imaging is an emerging tumor biomarker with unknown repeatability.  • The repeatability of deuterium metabolic imaging is on par with FDG-PET.  • The study of deuterium metabolic imaging in clinical populations is feasible.

Risk of Ovarian Malignancy Algorithm and Pelvic Mass Score for the prediction of malignant ovarian tumors: a prospective comparative study.

Aim: Ovarian cancer is the seventh most common female cancer worldwide. Nevertheless, there is no available universal screening method for malignant ovarian masses. This study compares the value of the Risk of Ovarian Malignancy Algorithm (ROMA) and Pelvic Mass Score (PMS) scoring systems in the diagnosis of malignant ovarian masses. Material and methods: This prospective comparative study was conducted from March 2021 until April 2022. A total of 258 women diagnosed with ovarian mass and eligible for surgical intervention according to institutional guidelines were enrolled in the study. Ultrasound was performed for the assessment of masses, ascites and metastases, also color flow Doppler was done to measure the resistance index of the mass vasculature. Preoperative venous blood samples were collected to measure CA 125 and HE4. PMS and ROMA scoring systems were calculated for each patient. All women were subjected to a surgical intervention (according to applicable institutional guidelines), using either open or laparoscopic techniques. Histopathological examination of the removed specimens was done, and in line with the recognized gold standard, the results were compared with the pre-operative diagnosis of both scoring systems. Results: Both PMS and ROMA showed a high predictive probability for ovarian malignancies (AUC = 0.93, sensitivity = 83.3%, specificity = 90.37%; AUC = 0.91, sensitivity = 84.4%, specificity = 95.56%, respectively), yet no statistical significant difference was found between the two scoring systems (p = 0.353, 95% CI -0.025 to 0.070). Conclusions: Both PMS and ROMA seem to be promising scoring systems for discriminating benign from malignant ovarian masses, but more research is needed to determine the optimum diagnostic pathway, especially one yielding the least false-negative results.

Genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune infiltrates of non-small cell lung cancer metastasis.

AIMS: To investigate the genomic discordances and heterogeneous mutational burden, PD-L1 expression and immune cell (IC) infiltrates of non-small cell lung cancer (NSCLC) metastasis. METHODS: Surgical samples from 41 cases of NSCLC with metastatic tumours (MTs) and paired primary tumours (PTs) were collected. PD-L1 expression and ICs were quantified using image-based immunohistochemistry profiling. Whole exome sequencing was employed to explore discrepancies in genomic characteristics, tumour mutational burden (TMB) and tumour neoantigen burden (TNB) in 28 cases. RESULTS: Non-synonymous mutations in MTs were slightly more than in PTs, with only 42.34% of mutations shared between paired PTs and MTs. The heterogeneity of TMB showed no significant difference (p=0.785) between MTs and PTs, while TNB significantly increased in MTs (p=0.013). MTs generally exhibited a higher density of PD-L1+ cells and a higher tumour proportion score with a lower density of IC infiltrates. Subgroup analysis considering clinicopathological factors revealed that the heterogeneity of immune biomarkers was closely associated with the histology of lung adenocarcinoma, metastatic sites of extrapulmonary, time intervals and treatment history. Prognosis analysis indicated that a high density of CD8+ T cells was a low-risk factor, whereas a high density of PD-L1+ cells in MTs was a high-risk factor for cancer-related death in metastatic NSCLC. CONCLUSIONS: The mutational burden, PD-L1 expression and IC infiltrates undergo changes during NSCLC metastasis, which may impact the immunotherapeutic benefits in patients with NSCLC with metastatic progression and should be monitored according to clinical scenarios.

Increased PI3K pathway activity is associated with recurrent breast cancer in patients with low and intermediate 21-gene recurrence score.

AIMS: We investigated key signalling pathways' activity and mutational status of early-stage breast carcinomas with low and intermediate 21-gene recurrence score (RS) to identify molecular features that may predict recurrence. METHODS: This is a retrospective case-control study of 18 patients with recurrent breast carcinoma with low and intermediate 21-gene RS (<25) and control group of 15 non-recurrent breast cancer patients. DNA and mRNA were extracted from tumour tissue. mRNA expression of genes involved in oestrogen receptor (ER), androgen receptor (AR), PI3K and MAPK signalling pathways was measured by real-time quantitative reverse transcription-qPCR (OncoSIGNal G4 test, InnoSIGN). Tumour mutational landscape was assessed by targeted DNA sequencing (Oncomine Precision Assay). RESULTS: There were no statistical differences between the groups' demographic and clinicopathological characteristics. PI3K pathway showed significantly higher activity in cases compared with controls (p=0.0014). Receiver operating characteristic curve analysis showed an area under the curve of 0.79 for PI3K pathway activity in the prediction of recurrent disease in low and intermediate 21-gene RS breast cancer. There was no difference in ER, AR and MAPK pathway activity. PIK3CA alterations were the most common driver mutations, but no difference was found between the groups (p=0.46) and no association with PI3K pathway activity (p=0.86). Higher Ki67 gene expression was associated with recurrences (p=0.042) CONCLUSION: Increased PI3K pathway activity, independent of PIK3CA mutations, may play a role in the recurrence of early-stage breast cancer with low and intermediate 21-gene RS. Pathway analysis can help to identify high-risk patients in this setting.

TCCIA: a comprehensive resource for exploring CircRNA in cancer immunotherapy.

BACKGROUND: Immunotherapies targeting immune checkpoints have gained increasing attention in cancer treatment, emphasizing the need for predictive biomarkers. Circular RNAs (circRNAs) have emerged as critical regulators of tumor immunity, particularly in the PD-1/PD-L1 pathway, and have shown potential in predicting immunotherapy efficacy. Yet, the detailed roles of circRNAs in cancer immunotherapy are not fully understood. While existing databases focus on either circRNA profiles or immunotherapy cohorts, there is currently no platform that enables the exploration of the intricate interplay between circRNAs and anti-tumor immunotherapy. A comprehensive resource combining circRNA profiles, immunotherapy responses, and clinical outcomes is essential to advance our understanding of circRNA-mediated tumor-immune interactions and to develop effective biomarkers. METHODS: To address these gaps, we constructed The Cancer CircRNA Immunome Atlas (TCCIA), the first database that combines circRNA profiles, immunotherapy response data, and clinical outcomes across multicancer types. The construction of TCCIA involved applying standardized preprocessing to the raw sequencing FASTQ files, characterizing circRNA profiles using an ensemble approach based on four established circRNA detection tools, analyzing tumor immunophenotypes, and compiling immunotherapy response data from diverse cohorts treated with immune checkpoint blockades (ICBs). RESULTS: TCCIA encompasses over 4,000 clinical samples obtained from 25 cohorts treated with ICBs along with other treatment modalities. The database provides researchers and clinicians with a cloud-based platform that enables interactive exploration of circRNA data in the context of ICB. The platform offers a range of analytical tools, including browse of identified circRNAs, visualization of circRNA abundance and correlation, association analysis between circRNAs and clinical variables, assessment of the tumor immune microenvironment, exploration of tumor molecular signatures, evaluation of treatment response or prognosis, and identification of altered circRNAs in immunotherapy-sensitive and resistant tumors. To illustrate the utility of TCCIA, we showcase two examples, including circTMTC3 and circMGA, by employing analysis of large-scale melanoma and bladder cancer cohorts, which unveil distinct impacts and clinical implications of different circRNA expression in cancer immunotherapy. CONCLUSIONS: TCCIA represents a significant advancement over existing resources, providing a comprehensive platform to investigate the role of circRNAs in immuno-oncology.

Plasma cell-free DNA hydroxymethylation profiling reveals anti-PD-1 treatment response and resistance biology in non-small cell lung cancer.

BACKGROUND: Treatment with immune checkpoint inhibitors (ICIs) targeting programmed death-1 (PD-1) can yield durable antitumor responses, yet not all patients respond to ICIs. Current approaches to select patients who may benefit from anti-PD-1 treatment are insufficient. 5-hydroxymethylation (5hmC) analysis of plasma-derived cell-free DNA (cfDNA) presents a novel non-invasive approach for identification of therapy response biomarkers which can tackle challenges associated with tumor biopsies such as tumor heterogeneity and serial sample collection. METHODS: 151 blood samples were collected from 31 patients with non-small cell lung cancer (NSCLC) before therapy started and at multiple time points while on therapy. Blood samples were processed to obtain plasma-derived cfDNA, followed by enrichment of 5hmC-containing cfDNA fragments through biotinylation via a two-step chemistry and binding to streptavidin coated beads. 5hmC-enriched cfDNA and whole genome libraries were prepared in parallel and sequenced to obtain whole hydroxymethylome and whole genome plasma profiles, respectively. RESULTS: Comparison of on-treatment time point to matched pretreatment samples from same patients revealed that anti-PD-1 treatment induced distinct changes in plasma cfDNA 5hmC profiles of responding patients, as judged by Response evaluation criteria in solid tumors, relative to non-responders. In responders, 5hmC accumulated over genes involved in immune activation such as inteferon (IFN)-γ and IFN-α response, inflammatory response and tumor necrosis factor (TNF)-α signaling, whereas in non-responders 5hmC increased over epithelial to mesenchymal transition genes. Molecular response to anti-PD-1 treatment, as measured by 5hmC changes in plasma cfDNA profiles were observed early on, starting with the first cycle of treatment. Comparison of pretreatment plasma samples revealed that anti-PD-1 treatment response and resistance associated genes can be captured by 5hmC profiling of plasma-derived cfDNA. Furthermore, 5hmC profiling of pretreatment plasma samples was able to distinguish responders from non-responders using T cell-inflamed gene expression profile, which was previously identified by tissue RNA analysis. CONCLUSIONS: These results demonstrate that 5hmC profiling can identify response and resistance associated biological pathways in plasma-derived cfDNA, offering a novel approach for non-invasive prediction and monitoring of immunotherapy response in NSCLC.

Association of a gene-expression subtype to outcome and treatment response in patients with recurrent/metastatic head and neck squamous cell carcinoma treated with nivolumab.

BACKGROUND: Immune checkpoint inhibitors have been approved and currently used in the clinical management of recurrent and metastatic head and neck squamous cell carcinoma (R/M HNSCC) patients. The reported benefit in clinical trials is variable and heterogeneous. Our study aims at exploring and comparing the predictive role of gene-expression signatures with classical biomarkers for immunotherapy-treated R/M HNSCC patients in a multicentric phase IIIb trial. METHODS: Clinical data were prospectively collected in Nivactor tiral (single-arm, open-label, multicenter, phase IIIb clinical trial in platinum-refractory HNSCC treated with nivolumab). Findings were validated in an external independent cohort of immune-treated HNSCC patients, divided in long-term and short-term survivors (overall survival >18 and <6 months since the start of immunotherapy, respectively). Pretreatment tumor tissue specimen from immunotherapy-treated R/M HNSCC patients was used for PD-L1 (Tumor Proportion Score; Combined Positive Score (CPS)) and Tumor Mutational Burden (Oncopanel TSO500) evaluation and gene expression profiling; classical biomarkers and immune signatures (retrieved from literature) were challenged in the NIVACTOR dataset. RESULTS: Cluster-6 (Cl6) stratification of NIVACTOR cases in high score (n=16, 20%) and low score (n=64, 80%) demonstrated a statistically significant and clinically meaningful improvement in overall survival in the high-score cases (p=0.00028; HR=4.34, 95% CI 1.84 to 10.22) and discriminative ability reached area under the curve (AUC)=0.785 (95% CI 0.603 to 0.967). The association of high-score Cl6 with better outcome was also confirmed in: (1) NIVACTOR progression-free survival (p=4.93E-05; HR=3.71, 95% CI 1.92 to 7.18) and objective-response-rate (AUC=0.785; 95% CI 0.603 to 0.967); (2) long survivors versus short survivors (p=0.00544). In multivariate Cox regression analysis, Cl6 was independent from Eastern Cooperative Oncology Group performance status, PDL1-CPS, and primary tumor site. CONCLUSIONS: These data highlight the presence of underlying biological differences able to predict survival and response following treatment with immunotherapy in platinum-refractory R/M HNSCC that could have translational implications improving treatment selection. TRIAL REGISTRATION NUMBER: EudraCT Number: 2017-000562-30.

Circulating IL-6 is associated with disease progression in BRAFwt metastatic melanoma patients receiving anti-PD-1 therapy.

AIMS: Despite efficacy of anti-PD-1 blockade in treatment of metastatic melanoma (MM), many patients achieve rapid disease progression (DP). Therefore, the aim of this study is to better define biomarkers for DP by analysing levels of circulating cytokines TGF-ß, IFN-γ, IL-6, IL-8 and IL-10 in MM patients prior to anti-PD-1 therapy. METHODS: Cytokine levels were evaluated before therapy with pembrolizumab in peripheral blood of BRAF wild-type (wt) MM patients by ELISA method. RESULTS: In this study, we give pretherapy levels for circulating TGF-ß, IFN-γ, IL-6, IL-8 and IL-10 in BRAFwt MM patients and analyse them according to metastasis stage (M1a+M1 b, M1c, M1d groups), lactate dehydrogenase (LDH) level and occurrence of DP. Increased IL-6 level was found in M1d group (central nervous system metastasis), while LDH+patients (LDH ≥460 IU/L) have increased IL-6 and IL-8 values that correlate with LDH level. Also, IL-6 correlates with C reactive protein values. Furthermore, patients with DP have significantly higher IL-6 level compared with non-DP patients. Conversely, the other analysed cytokines are similar in investigated groups of MM patients. By receiver operating characteristics curve analysis, pretherapy IL-6 level was found to be a biomarker for the occurrence of DP with cut-off value of 3.02 pg/mL. Patients in M1d stage are prevalent in the group with IL-6 ≥3.02 pg/mL that is characterised with reduced progression-free survival and higher pretherapy IL-8 and LDH. CONCLUSION: The evidence in this study implies that baseline IL-6 could be a biomarker of DP and poor prognosis in BRAFwt MM patients treated with pembrolizumab.

Comparison of assessment of programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer biopsies and surgical specimens.

AIMS: Programmed death-ligand 1 (PD-L1) status in triple-negative breast cancer (TNBC) is important for immune checkpoint inhibitor therapies but may vary between different immunohistochemical assays, scorings and the type of specimen used for analysis. METHODS: We compared the analytical concordance of three clinically relevant PD-L1 assays (VENTANA SP142, VENTANA SP263 and DAKO 22C3 pharmDx) assessing immune cell score (IC), tumour proportion score and combined positive score (CPS) in preoperative biopsies and resection specimens of primary TNBC. PD-L1 expression was scored on virtual whole slide images and compared with expression data from corresponding surgical specimens. RESULTS: The mean PD-L1 positivity in TNBC biopsies defined as IC ≥1% and CPS ≥1 ranged between 11% and 61% with the lowest positivity for SP142 and highest for SP263. The corresponding surgical specimens showed overall higher positivity rates (53%-75%). When comparing biopsies with surgical specimens, the agreement for PD-L1 positivity with SP263 and 22C3 at IC score ≥1% and CPS ≥1 was fair (kappa 0.47-0.52) and poor for SP142 (kappa 0.15-0.19). Using CPS ≥10 cut-off, the agreement for SP263 was excellent (kappa 0.751) but poor for 22C3 (kappa 0.261). Spearman correlation coefficients ranged between 0.489 and 0.75 indicating a generally moderate to strong correlation between biopsies and surgical specimens for all assays and scores. CONCLUSIONS: We demonstrate high accordance between biopsies and surgical specimens for SP263 and 22C3 scoring but less for SP142. Generally, biopsies are suitable for PD-L1 testing in TNBC but the appropriate assay, scoring and cut-off must be considered.

Basal or stimulated thyroglobulin in evaluating response to treatment in papillary thyroid carcinoma? A retrospective cohort study.

OBJECTIVE: It is not clear whether response to initial treatment in papillary thyroid carcinoma (PTC) patients is best evaluated by measuring thyroglobulin (Tg) in the presence of levothyroxine (BTg) or when stimulated by elevated TSH (STg). The aim of this study was to evaluate whether response to therapy 1 year after initial treatment changes with the use of STg in relation to BTg in PTC patients treated with total thyroidectomy (TT) and radioiodine (131I), and, if observed, to assess which response is better associated with clinical course. SUBJECTS AND METHODS: This is a retrospective study of 148 PTC patients submitted to TT and 131I. We analyzed the response to therapy (excellent, biochemical incomplete, or indeterminate) at 1 year after initial treatment, using BTg or STg, and compared which method was better associated with "excellent response at final evaluation." RESULTS: Twenty-eight patients (20.4%) presented change in response to therapy, with 17 of these (60.7%) presenting a worse response. Response using STg was 1.6 times better associated with proposed outcome [odds ratio (OR) = 4.61; confidence interval 95% (IC95%): 2.13-9.98] than with BTg (OR = 2.84; IC95%: 1.33-6.06). CONCLUSION: Response to therapy at 1 year using STg was altered in approximately 20% of cases and therefore proved to be a better predictor of excellent response in the last evaluation.

Kinase expression in angiomatoid fibrous histiocytoma: panTRK is commonly expressed in the absence of NTRK rearrangement.

Angiomatoid fibrous histiocytoma (AFH) is a soft tissue tumour of intermediate (rarely metastasising) malignant potential, which harbours EWSR1/FUS gene fusions. These tumours can express anaplastic lymphoma kinase (ALK) in the absence of gene rearrangement or copy number alteration and can also coexpresses Pan-TRK immunohistochemistry (IHC). All EWSR1/FUS-rearranged AFH were retrieved from the files of three institutions and Pan-TRK (EPR17341), ALK and BRAF V600E IHC were performed. Fourteen AFH cases were identified, which included three cases of intracranial mesenchymal tumours with FET-CREB fusions. PanTRK and ALK positive immunostaining was identified in 9 (64.2%) and 12 (85.7%) cases, respectively. No NTRK or ALK translocations or increased copy number/amplification were identified in all eight cases which had fluorescence in situ hybridisation and/or next generation sequencing for NTRK1-3 and ALK available for assessment. None of the cases expressed BRAF-V600E.Although our study is limited, our report is the first to document PanTRK expression in AFH in the absence of identifiable NTRK1-3 gene alterations.

Machine-learning-based image analysis algorithms improve interpathologist concordance when scoring PD-L1 expression in non-small-cell lung cancer.

Programmed death ligand 1 (PD-L1) expression on tumour cells is the only predictive biomarker of response to immuno-modulatory therapy for patients with non-small-cell lung cancer (NSCLC). Accuracy of this biomarker is hampered by its challenging interpretation. Here we explore if the use of machine-learning derived image analysis tools can improve interpathologist concordance of assessing PD-L1 expression in NSCLC.Five pathologists who routinely score PD-L1 at a major regional referral hospital for thoracic surgery participated. 13 NSCLC small diagnostic biopsies were stained for PD-L1 (SP263 clone) and digitally scanned. Each pathologist independently scored each case with and without the Roche uPath PD-L1 (SP263) image analysis NSCLC algorithm with a wash-out interim period of 6 weeks.A consistent improvement in interpathologist concordance was seen when using the image analysis tool compared with scoring without: (Fleiss' kappa 0.886 vs 0.613 (p<0.0001) and intraclass coefficient correlation 0.954 vs 0.837 (p<0.001)). Five cases (38%) were classified into clinically relevant different categories (negative/weak/strong) by multiple pathologists when not using the image analysis algorithm, whereas only two cases (15%) were classified differently when using the image analysis algorithm.The use of the image analysis algorithm improved the concordance of assessing PD-L1 expression between pathologists. Critically, there was a marked improvement in the placement of cases into more consistent clinical groupings. This small study is evidence that the use of image analysis tools may improve consistency in assessing tumours for PD-L1 expression and may therefore result in more consistent prediction to targeted treatment options.