Unleashing Natural IL18 Activity Using an Anti-IL18BP Blocker Induces Potent Immune Stimulation and Antitumor Effects

Recombinant cytokines have limited anticancer efficacy mostly due to a narrow therapeutic window and systemic adverse effects. IL18 is an inflammasome-induced proinflammatory cytokine, which enhances T- and NK-cell activity and stimulates IFNγ production. The activity of IL18 is naturally blocked by a high-affinity endogenous binding protein (IL18BP). IL18BP is induced in the tumor microenvironment (TME) in response to IFNγ upregulation in a negative feedback mechanism. In this study, we found that IL18 is upregulated in the TME compared with the periphery across multiple human tumors and most of it is bound to IL18BP. Bound IL18 levels were largely above the amount required for T-cell activation in vitro, implying that releasing IL18 in the TME could lead to potent T-cell activation. To restore the activity of endogenous IL18, we generated COM503, a high-affinity anti-IL18BP that blocks the IL18BP:IL18 interaction and displaces precomplexed IL18, thereby enhancing T- and NK-cell activation. In vivo, administration of a surrogate anti-IL18BP, either alone or in combination with anti-PD-L1, resulted in significant tumor growth inhibition and increased survival across multiple mouse tumor models. Moreover, the anti-IL18BP induced pronounced TME-localized immune modulation including an increase in polyfunctional nonexhausted T- and NK-cell numbers and activation. In contrast, no increase in inflammatory cytokines and lymphocyte numbers or activation state was observed in serum and spleen. Taken together, blocking IL18BP using an Ab is a promising approach to harness cytokine biology for the treatment of cancer.

Plasma Proteome-Based Test for First-Line Treatment Selection in Metastatic Non-Small Cell Lung Cancer

PURPOSE

Current guidelines for the management of metastatic non-small cell lung cancer (NSCLC) without driver mutations recommend checkpoint immunotherapy with PD-1/PD-L1 inhibitors, either alone or in combination with chemotherapy. This approach fails to account for individual patient variability and host immune factors and often results in less-than-ideal outcomes. To address the limitations of the current guidelines, we developed and subsequently blindly validated a machine learning algorithm using pretreatment plasma proteomic profiles for personalized treatment decisions.

PATIENTS AND METHODS

We conducted a multicenter observational trial (ClinicalTrials.gov identifier: NCT04056247) of patients undergoing PD-1/PD-L1 inhibitor-based therapy (n = 540) and an additional patient cohort receiving chemotherapy (n = 85) who consented to pretreatment plasma and clinical data collection. Plasma proteome profiling was performed using SomaScan Assay v4.1.

RESULTS

Our test demonstrates a strong association between model output and clinical benefit (CB) from PD-1/PD-L1 inhibitor-based treatments, evidenced by high concordance between predicted and observed CB (R2 = 0.98, P < .001). The test categorizes patients as either PROphet-positive or PROphet-negative and further stratifies patient outcomes beyond PD-L1 expression levels. The test successfully differentiates between PROphet-negative patients exhibiting high tumor PD-L1 levels (≥50%) who have enhanced overall survival when treated with a combination of immunotherapy and chemotherapy compared with immunotherapy alone (hazard ratio [HR], 0.23 [95% CI, 0.1 to 0.51], P = .0003). By contrast, PROphet-positive patients show comparable outcomes when treated with immunotherapy alone or in combination with chemotherapy (HR, 0.78 [95% CI, 0.42 to 1.44], P = .424).

CONCLUSION

Plasma proteome-based testing of individual patients, in combination with standard PD-L1 testing, distinguishes patient subsets with distinct differences in outcomes from PD-1/PD-L1 inhibitor-based therapies. These data suggest that this approach can improve the precision of first-line treatment for metastatic NSCLC.

Biological insights from plasma proteomics of non-small cell lung cancer patients treated with immunotherapy

Introduction

Immune checkpoint inhibitors have made a paradigm shift in the treatment of non-small cell lung cancer (NSCLC). However, clinical response varies widely and robust predictive biomarkers for patient stratification are lacking. Here, we characterize early on-treatment proteomic changes in blood plasma to gain a better understanding of treatment response and resistance.

Methods

Pre-treatment (T0) and on-treatment (T1) plasma samples were collected from 225 NSCLC patients receiving PD-1/PD-L1 inhibitor-based regimens. Plasma was profiled using aptamer-based technology to quantify approximately 7000 plasma proteins per sample. Proteins displaying significant fold changes (T1:T0) were analyzed further to identify associations with clinical outcomes using clinical benefit and overall survival as endpoints. Bioinformatic analyses of upregulated proteins were performed to determine potential cell origins and enriched biological processes.

Results

The levels of 142 proteins were significantly increased in the plasma of NSCLC patients following ICI-based treatments. Soluble PD-1 exhibited the highest increase, with a positive correlation to tumor PD-L1 status, and, in the ICI monotherapy dataset, an association with improved overall survival. Bioinformatic analysis of the ICI monotherapy dataset revealed a set of 30 upregulated proteins that formed a single, highly interconnected network, including CD8A connected to ten other proteins, suggestive of T cell activation during ICI treatment. Notably, the T cell-related network was detected regardless of clinical benefit. Lastly, circulating proteins of alveolar origin were identified as potential biomarkers of limited clinical benefit, possibly due to a link with cellular stress and lung damage.

Conclusions

Our study provides insights into the biological processes activated during ICI-based therapy, highlighting the potential of plasma proteomics to identify mechanisms of therapy resistance and biomarkers for outcome.

Erythropoietin-producing hepatocellular receptor B6 is highly expressed in non-functioning pituitary neuroendocrine tumors and its expression correlates with tumor size

BACKGROUND

Erythropoietin-producing hepatocellular (EPH) receptors are the largest known family of receptor tyrosine kinases characterized in humans. These proteins are involved in tissue organization, synaptic plasticity, vascular development and the progression of various diseases including cancer. The Erythropoietin-producing hepatocellular receptor tyrosine kinase member EphB6 is a pseudokinase which has not attracted an equivalent amount of interest as its enzymatically-active counterparts. The aim of this study was to assess the expression of EphB6 in pituitary tumors.

METHODS AND RESULTS

Human normal pituitaries and pituitary tumors were examined for EphB6 mRNA expression using real-time PCR and for EphB6 protein by immunohistochemistry and Western blotting. EphB6 was highly expressed in non-functioning pituitary neuroendocrine tumors (NF-PitNETs) versus the normal pituitary and GH-secreting PitNETs. EphB6 mRNA expression was correlated with tumor size.

CONCLUSIONS

Our results suggest EphB6 aberrant expression in NF-PitNETs. Future studies are warranted to determine the role and significance of EphB6 in NF-PitNETs tumorigenesis.

Serologic Response and Safety after a Third Dose of the COVID-19 BNT162b2 Vaccine in Patients with Inflammatory Bowel Diseases

Vaccines are pivotal for control of the coronavirus disease (COVID-19) pandemic. Patients with inflammatory bowel diseases (IBDs) treated with antitumor necrosis factor (TNF)-α have lower serologic response after two COVID-19 vaccine doses. Data regarding a third vaccine dose are scarce. An Israeli multicenter prospective observational study recruited 319 subjects: 220 with IBD (79 treated with anti-TNFα) and 99 healthy control (HC) participants. All patients received two mRNA-BNT162b2 vaccines (Pfizer/BioNTech), 80% of whom received a third vaccine dose. Evaluation included disease activity, anti-spike (S) and nucleocapsid (N) antibody levels, anti-TNFα drug levels, and adverse events (AEs). All participants showed significant serologic response one month after receiving a third dose. However, three months later, the anti-S levels decreased significantly in patients treated with anti-TNFα compared with the non-anti-TNFα and HC groups. A correlation between serologic response to the third vaccine dose and anti-TNF drug levels was not found. No significant AE or IBD exacerbation was observed. Importantly, lower serologic response after the third vaccine dose predicted infection. A third dose of BNT162b2 is effective and safe in patients with IBD. Lower serologic response predicted infection, even in seropositive subjects. Lower serologic responses and their rapid decline suggest a fourth vaccine dose in this patient population.

Blood-Derived Exosomal hTERT mRNA in Patients with Lung Cancer: Characterization and Correlation with Response to Therapy

Background: Telomerase (human telomerase reverse transcriptase (hTERT) is considered a hallmark of cancer, being active in cancer cells but repressed in human somatic cells. As such, it has the potential to serve as a valid cancer biomarker. Exosomal hTERT mRNA can be detected in the serum of patients with solid malignancies but not in healthy individuals. We sought to evaluate the feasibility of measuring serum exosomal hTERT transcripts levels in patients with lung cancer. Methods: A prospective analysis of exosomal hTERT mRNA levels was determined in serum-derived exosomes from 76 patients with stage III-IV lung cancer (11 SCLC and 65 NSCLC). An hTERT level above RQ = 1.2 was considered "detectable" according to a previous receiver operating characteristic curve (ROC) curve. Sequential measurements were obtained in 33 patients. Demographic and clinical data were collected retrospectively from patients' charts. Data on response to systemic therapy (chemotherapy, immunotherapy, and tyrosine kinase inhibitors) were collected by the treating physicians. Results: hTERT was detected in 53% (40/76) of patients with lung cancer (89% of SCLC and 46% of NSLCC). The mean hTERT levels were 3.7 in all 76 patients, 5.87 in SCLC patients, and 3.62 in NSCLC patients. In total, 25 of 43 patients with sequential measurements had detectable levels of hTERT. The sequential exosomal hTERT mRNA levels reflected the clinical course in 23 of them. Decreases in hTERT levels were detected in 17 and 5 patients with partial and complete response, respectively. Eleven patients with a progressive disease had an increase in the level of exosomal hTERT, and seven with stable disease presented increases in its exosomal levels. Another patient who progressed on the first line of treatment and had a partial response to the second line of treatment exhibited an increase in exosomal hTERT mRNA levels during the progression and a decrease during the response. Conclusions: Exosomal hTERT mRNA levels are elevated in over half of patients with lung cancer. The potential association between hTERT levels and response to therapy suggests its utility as a promising cancer biomarker for response to therapy. This issue should be further explored in future studies.

Abstract 2159: A pretreatment blood-based proteomic biomarker for enhanced decision-making in non-small cell lung cancer

Introduction: Treatment modality selection for metastatic NSCLC patients (immunotherapy alone vs. combination of immunotherapy with chemotherapy) relies mainly on determining the programmed cell death 1 (PD-L1) expression levels in the tumor. However, available assays are only moderately predictive. Here we set to develop PROphet®, a plasma proteomics-based predictive model for informing treatment decisions for NSCLC patients receiving immune checkpoint inhibitor (ICI)-based therapy.

Methods: Pre-ICI plasma samples were collected in 12 centers in a clinical trial (NCT04056247) from 367 advanced-stage NSCLC patients. Clinical benefit (CB) was assessed at 12 months based on the occurrence of progression-free survival (PFS) until this time point. Deep proteomic profiling of the plasma samples was performed using aptamer-based technology. A novel machine learning model was developed to determine the CB probability for each patient, and the performance was successfully evaluated on an independent validation set, followed by training and prediction over the entire cohort using cross-validation. The resulting PROphet® score (positive or negative) was determined by setting the median CB rate probability as a threshold. The patients were divided into four subgroups based on their PD-L1 expression level combined with their PROphet® score prediction, and the overall survival (OS) was examined for each subgroup.

Results: The PROphet® computational model was evaluated in a blinded manner on a subset of 85 patients and displayed strong predictive capability with area under the curve (AUC) of the receiver operating characteristics (ROC) plot of 0.78 (p-value = 5.00e-05), outperforming a PD-L1-based predictive model (AUC = 0.62; p-value 2.76e-01). When combining PROphet® score with PD-L1 expression levels, four different outcome patterns were identified: (i) Patients with PD-L1 ≥50% and PROphet® negative score, who displayed significantly longer OS when treated with ICI-chemotherapy combination therapy compared to ICI monotherapy and may consider combination therapy. (ii) Patients with PD-L1 ≥50% and PROphet® positive score, who benefit similarly from either treatment modalities, and may consider monotherapy to avoid the potential toxicity of the combination therapy. (iii) Patients with PD-L1&lt;50% and PROphet® negative score, who do not benefit from either treatment modalities and may consider chemotherapy alone or treatment beyond standard of care. (iv) Patients with PD-L1&lt;50% and PROphet® positive score who benefit from combination therapy.

Conclusions: Altogether, the PROphet® model, when combined with PD-L1 test, stratifies the patients into four subgroups, providing additional resolution to the PD-L1 biomarker currently used to guide treatment selection. Furthermore, the model accurately predicts CB at 12 months based on proteomic analysis of a pre-treatment plasma sample.

Citation Format: Michal Harel, Petros Christopoulos, Coren Lahav, Itamar Sela, Nili Dahan, Niels Reinmuth, Ina Koch, Alona Zer, Mor Moskovitz, Adva Levy-Barda, Michal Lotem, Hovav Nechushtan, Rivka Katzenelson, Abed Agbarya, Mahmoud Abu-Amna, Maya Gottfried, Ido Wolf, Ella Tepper, Yanyan Lou, Raya Leibowitz, Adam P. Dicker, David Gandara, David P. Carbone. A pretreatment blood-based proteomic biomarker for enhanced decision-making in non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 2159.

Altered somatic hypermutation patterns in COVID-19 patients classifies disease severity

Introduction

The success of the human body in fighting SARS-CoV2 infection relies on lymphocytes and their antigen receptors. Identifying and characterizing clinically relevant receptors is of utmost importance.

Methods

We report here the application of a machine learning approach, utilizing B cell receptor repertoire sequencing data from severely and mildly infected individuals with SARS-CoV2 compared with uninfected controls.

Results

In contrast to previous studies, our approach successfully stratifies non-infected from infected individuals, as well as disease level of severity. The features that drive this classification are based on somatic hypermutation patterns, and point to alterations in the somatic hypermutation process in COVID-19 patients.

Discussion

These features may be used to build and adapt therapeutic strategies to COVID-19, in particular to quantitatively assess potential diagnostic and therapeutic antibodies. These results constitute a proof of concept for future epidemiological challenges.

Human intestinal epithelial cells can internalize luminal fungi via LC3-associated phagocytosis

Background

Intestinal epithelial cells (IECs) are the first to encounter luminal microorganisms and actively participate in intestinal immunity. We reported that IECs express the β-glucan receptor Dectin-1, and respond to commensal fungi and β-glucans. In phagocytes, Dectin-1 mediates LC3-associated phagocytosis (LAP) utilizing autophagy components to process extracellular cargo. Dectin-1 can mediate phagocytosis of β-glucan-containing particles by non-phagocytic cells. We aimed to determine whether human IECs phagocytose β-glucan-containing fungal particles via LAP.

Methods

Colonic (n=18) and ileal (n=4) organoids from individuals undergoing bowel resection were grown as monolayers. Fluorescent-dye conjugated zymosan (β-glucan particle), heat-killed- and UV inactivated C. albicans were applied to differentiated organoids and to human IEC lines. Confocal microscopy was used for live imaging and immuno-fluorescence. Quantification of phagocytosis was carried out with a fluorescence plate-reader.

Results

zymosan and C. albicans particles were phagocytosed by monolayers of human colonic and ileal organoids and IEC lines. LAP was identified by LC3 and Rubicon recruitment to phagosomes and lysosomal processing of internalized particles was demonstrated by co-localization with lysosomal dyes and LAMP2. Phagocytosis was significantly diminished by blockade of Dectin-1, actin polymerization and NAPDH oxidases.

Conclusions

Our results show that human IECs sense luminal fungal particles and internalize them via LAP. This novel mechanism of luminal sampling suggests that IECs may contribute to the maintenance of mucosal tolerance towards commensal fungi.

Three-month follow-up of durability of response to the third dose of the SARS-CoV-2 BNT162b2 vaccine in adults aged 60 years and older: a prospective cohort study

OBJECTIVE

To evaluate the durability of response 3 months after the third BNT162b2 vaccine in adults aged 60 years and older.

DESIGN

Prospective cohort study.

SETTING

Single tertiary centre.

PARTICIPANTS

Healthcare workers/family members aged ≥60 years old who received the third BNT162b2 dose.

INTERVENTIONS

Blood samples were drawn immediately before (T0), 10-19 days (T1) and 74-103 days (T2) after the third dose.

PRIMARY AND SECONDARY OUTCOME MEASURES

Anti-spike IgG titres were determined using a commercial assay and seropositivity was defined as ≥50 arbitrary units (AU)/mL. Neutralising antibody titres were determined at T2. Adverse events, COVID-19 infections and Clinical Frailty Scale (CFS) levels were documented.

RESULTS

The analysis included 97 participants (median age, 70 years (IQR, 66-74), 58% CFS level 2). IgG titres, which increased significantly from T0 to T1 (median, 440 AU/mL (IQR, 294-923) and median, 25 429 AU/mL (IQR, 14 203-36 114), respectively; p<0.001), decreased significantly by T2, but all remained seropositive (median, 8306 AU/mL (IQR, 4595-14 701), p<0.001 vs T1). In a multivariable analysis, only time from the second vaccine was significantly associated with lower IgG levels at T2 (p=0.017). At T2, 60 patients were evaluated for neutralising antibodies; all were seropositive (median, 1294 antibody titres; IQR, 848-2072). Neutralising antibody and anti-spike IgG levels were correlated (r=0.6, p<0.001). No major adverse events or COVID-19 infections were reported.

CONCLUSIONS

Anti-spike IgG and neutralising antibody levels remain adequate 3 months after the third BNT162b2 vaccine in healthy adults aged ≥60 years, although the decline in IgG is concerning. A third dose of vaccine in this population should be top priority.

Personalized approach for response prediction and treatment management for non-small cell lung cancer patients based on a liquid biopsy

e21132

Background: To date, predicting response to immune checkpoint blockade (ICB) therapy in non-small cell lung cancer (NSCLC) patients is based on assessing PD-L1 levels in tumor biopsies. However, such assays are only moderately predictive. In addition, the assays require a tumor biopsy and do not aid in identifying patient-specific resistance mechanisms beyond PD-L1. To overcome these issues, we developed a novel computational approach for predicting response to ICB based on pre-treatment proteomic measurements in liquid biopsies. Methods: Plasma samples were collected from 184 NSCLC patients prior to treatment, along with comprehensive clinical data, as part of an ongoing multi-center clinical trial (PROPHETIC; NCT04056247). Overall response rate (ORR) was assessed 3- and 6-months following treatment initiation. A deep proteomic profiling of each plasma sample was performed, measuring the expression levels of approximately 7000 proteins. A novel proprietary machine learning approach was developed on a subset of samples (training set; n = 110) and then was tested on a blind independent validation set (n = 74). Results: A computational model was developed on the proteomic data by identifying patient-specific Resistance Associated Proteins (RAPs). Focusing on differentially expressed proteins between responders and non-responders, a protein was defined as a RAP in a given patient based on its expression level in the patient relative to the expression distribution of the RAP in responders and non-responders. The probability of response to ICB treatment was determined based on the patient’s RAP profile together with 4 clinical parameters. The RAP-based machine learning model successfully stratified between patients with prolonged and limited benefit with a hazard ratio (HR) of 4.5 (confidence interval 2.07-9.77; p-value < 0.0001) and 2.27 (confidence interval 1.7-4.03; p-value = 0.004) for overall survival and progression free survival, respectively. Each patient displayed a resistance map comprised of a unique combination of RAPs, suggesting a new approach for personalized medicine based on patient-specific pathway blockade. For example, a patient with KDR and IL-6 defined as RAPs may benefit from a clinical trial that targets any of these RAPS in combination with ICB. Last, an exploration into the biological functions of the identified RAPs revealed specific biological processes in each response group, including splicing, complement system, coagulation and signaling. Conclusions: We have developed a novel computational approach based on proteomic profiling of liquid biopsies for predicting response to ICB treatment in NSCLC patients. Our approach also sheds light on patient-specific resistance mechanisms, potentially enabling personalized treatment options and patient monitoring over time.

Lower Serologic Response to COVID-19 mRNA Vaccine in Patients With Inflammatory Bowel Diseases Treated With Anti-TNFα

BACKGROUND & AIM

Patients with inflammatory bowel diseases (IBD), specifically those treated with anti-tumor necrosis factor (TNF)α biologics, are at high risk for vaccine-preventable infections. Their ability to mount adequate vaccine responses is unclear. The aim of the study was to assess serologic responses to messenger RNA-Coronavirus Disease 2019 vaccine, and safety profile, in patients with IBD stratified according to therapy, compared with healthy controls (HCs).

METHODS

Prospective, controlled, multicenter Israeli study. Subjects enrolled received 2 BNT162b2 (Pfizer/BioNTech) doses. Anti-spike antibody levels and functional activity, anti-TNFα levels and adverse events (AEs) were detected longitudinally.

RESULTS

Overall, 258 subjects: 185 IBD (67 treated with anti-TNFα, 118 non-anti-TNFα), and 73 HCs. After the first vaccine dose, all HCs were seropositive, whereas ∼7% of patients with IBD, regardless of treatment, remained seronegative. After the second dose, all subjects were seropositive, however anti-spike levels were significantly lower in anti-TNFα treated compared with non-anti-TNFα treated patients, and HCs (both P < .001). Neutralizing and inhibitory functions were both lower in anti-TNFα treated compared with non-anti-TNFα treated patients, and HCs (P < .03; P < .0001, respectively). Anti-TNFα drug levels and vaccine responses did not affect anti-spike levels. Infection rate (∼2%) and AEs were comparable in all groups. IBD activity was unaffected by BNT162b2.

CONCLUSIONS

In this prospective study in patients with IBD stratified according to treatment, all patients mounted serologic response to 2 doses of BNT162b2; however, its magnitude was significantly lower in patients treated with anti-TNFα, regardless of administration timing and drug levels. Vaccine was safe. As vaccine serologic response longevity in this group may be limited, vaccine booster dose should be considered.

Detection of gene mutations and gene-gene fusions in circulating cell-free DNA of glioblastoma patients: an avenue for clinically relevant diagnostic analysis

Glioblastoma (GBM) is the most common type of glioma and is uniformly fatal. Currently, tumour heterogeneity and mutation acquisition are major impedances for tailoring personalized therapy. We collected blood and tumour tissue samples from 25 GBM patients and 25 blood samples from healthy controls. Cell‐free DNA (cfDNA) was extracted from the plasma of GBM patients and from healthy controls. Tumour DNA was extracted from fresh tumour samples. Extracted DNA was sequenced using a whole‐genome sequencing procedure. We also collected 180 tumour DNA datasets from GBM patients publicly available at the TCGA/PANCANCER project. These data were analysed for mutations and gene–gene fusions that could be potential druggable targets. We found that plasma cfDNA concentrations in GBM patients were significantly elevated (22.6 ± 5 ng·mL⁻¹), as compared to healthy controls (1.4 ± 0.4 ng·mL⁻¹) of the same average age. We identified unique mutations in the cfDNA and tumour DNA of each GBM patient, including some of the most frequently mutated genes in GBM according to the COSMIC database (TP53, 18.75%; EGFR, 37.5%; NF1, 12.5%; LRP1B, 25%; IRS4, 25%). Using our gene–gene fusion database, ChiTaRS 5.0, we identified gene–gene fusions in cfDNA and tumour DNA, such as KDR–PDGFRA and NCDN–PDGFRA, which correspond to previously reported alterations of PDGFRA in GBM (44% of all samples). Interestingly, the PDGFRA protein fusions can be targeted by tyrosine kinase inhibitors such as imatinib, sunitinib, and sorafenib. Moreover, we identified BCR–ABL1 (in 8% of patients), COL1A1–PDGFB (8%), NIN–PDGFRB (8%), and FGFR1–BCR (4%) in cfDNA of patients, which can be targeted by analogues of imatinib. ROS1 fusions (CEP85L–ROS1 and GOPC–ROS1), identified in 8% of patient cfDNA, might be targeted by crizotinib, entrectinib, or larotrectinib. Thus, our study suggests that integrated analysis of cfDNA plasma concentration, gene mutations, and gene–gene fusions can serve as a diagnostic modality for distinguishing GBM patients who may benefit from targeted therapy. These results open new avenues for precision medicine in GBM, using noninvasive liquid biopsy diagnostics to assess personalized patient profiles. Moreover, repeated detection of druggable targets over the course of the disease may provide real‐time information on the evolving molecular landscape of the tumour.

Evaluation of Seropositivity Following BNT162b2 Messenger RNA Vaccination for SARS-CoV-2 in Patients Undergoing Treatment for Cancer

Importance

Patients with cancer undergoing treatment are at high risk of COVID-19 following SARS-CoV-2 infection; however, their ability to produce an adequate antibody response to messenger RNA SARS-CoV-2 vaccines is unclear.

Objective

To evaluate rates of antispike (anti-S) antibody response to a BNT162b2 vaccine in patients with cancer who are undergoing systemic treatment vs healthy controls.

Design, Setting, and Participants

This prospective cohort study included 102 adult patients with solid tumors undergoing active intravenous anticancer treatment and 78 controls who received the second dose of the BNT162b2 vaccine at least 12 days before enrollment. The controls were taken from a convenience sample of the patients' family/caregivers who accompanied them to treatment. The study was conducted between February 22, 2021, and March 15, 2021 at Davidoff Cancer Center at Beilinson Hospital (Petah Tikva, Israel).

Interventions

Blood samples were drawn from the study participants. Serum samples were analyzed and the titers of the IgG antibodies against SARS-CoV-2 spike receptor-binding domain were determined using a commercially available immunoassay. Seropositivity was defined as 50 or greater AU/mL.

Main Outcomes and Measures

The primary outcome was the rate of seropositivity. Secondary outcomes included comparisons of IgG titers and identifying factors that were associated with seropositivity using univariate/multivariable analyses.

Results

The analysis included 180 participants, which comprised 102 patients with cancer (median [interquartile range (IQR)] age, 66 [56-72] years; 58 men [57%]) and 78 healthy controls (median [IQR] age, 62 [49-70] years; 25 men [32%]). The most common tumor type was gastrointestinal (29 [28%]). In the patient group, 92 (90%) were seropositive for SARS-CoV 2 antispike IgG antibodies after the second vaccine dose, whereas in the control group, all were seropositive. The median IgG titer in the patients with cancer was significantly lower than that in the controls (1931 [IQR, 509-4386] AU/mL vs 7160 [IQR, 3129-11 241] AU/mL; P < .001). In a multivariable analysis, the only variable that was significantly associated with lower IgG titers was treatment with chemotherapy plus immunotherapy (β, -3.5; 95% CI, -5.6 to -1.5).

Conclusions and Relevance

In this cohort study of patients with cancer who were receiving active systemic therapy, 90% of patients exhibited adequate antibody response to the BNT162b2 vaccine, although their antibody titers were significantly lower than those of healthy controls. Further research into the clinical relevance of lower titers and their durability is required. Nonetheless, the data support vaccinating patients with cancer as a high priority, even during therapy.

PATH-24. DETECTION OF POINT MUTATIONS AND GENE FUSIONS FROM CIRCULATING CELL-FREE DNA (CFDNA) OF GLIOBLASTOMA (GBM) PATIENTS

BACKGROUND

GBM is characterized by intratumoral heterogeneity. Tumor heterogeneity, clonal diversity and mutation acquisition hamper the ability to tailor personalized therapy for GBM. Tumor sampling has limited ability to accurately capture the molecular landscape of the tumor and to disclose acquired molecular aberrations. Mutation analysis of cfDNA is a non-invasive procedure which may overcome these limitations as it may reflect the real composition of the tumor and track the molecular evolution. We sequenced cfDNA of GBM patients and assessed mutation patterns and fusion genes.

METHODS

We collected blood and respective tumor samples from 27 GBM patients and blood samples from 14 healthy controls. Tumor DNA, cfDNA and WBC DNA were sequenced using deep sequencing procedures. The data were analyzed for detection of single nucleotide polymorphism (SNPs) and gene-gene fusions.

RESULTS

GBM cfDNA concentrations were significantly elevated (median: 23.63 ng/mL; range 12.6–137) compared to healthy controls (median 2.06; range 1.68–7.62) (p &lt; 0.0001). We identified unique SNPs in each glioma patient’s cfDNA and the corresponding tumor DNA including the top-10 most frequently mutated genes in GBM. For example, mutation of TP53 was detected in18.75%; EGFR in 37.5%; NF1-12.5%; LRP1B-25% and IRS4 in 25%. For gene-gene fusion we used the in-house fusion gene database, ChiTaRS 5.0, and identified fusions in cfDNA and tumor DNA. Thus, KMT2A-FLNA was the most frequent fusion found in 16.4% of samples. BCR-ABL1 in 8.82% and FGFR1-BCR in 2.94%. Other fusions included COL1A1-PDGFB (5.88%), NIN-PDGFRB (5.88%), KIF5B-RET (5.88%) and also TPM3-ROS1(2.94%), TFG-ALK(2.94%), MSN-ALK (2.94%) and NPM1-ALK (2.94%) which may be targeted by brain penetrating drugs that are ROS1 and ALK inhibitors.

CONCLUSIONS

Our study suggests that plasma cfDNA analysis may help to uncover real time mutational and gene fusion status of GBM by a non-invasive procedure. It may identify drug targets based on personalized gene-gene fusions.

The Ubiquitin E3/E4 Ligase UBE4A Adjusts Protein Ubiquitylation and Accumulation at Sites of DNA Damage, Facilitating Double-Strand Break Repair

Double-strand breaks (DSBs) are critical DNA lesions that robustly activate the elaborate DNA damage response (DDR) network. We identified a critical player in DDR fine-tuning: the E3/E4 ubiquitin ligase UBE4A. UBE4A's recruitment to sites of DNA damage is dependent on primary E3 ligases in the DDR and promotes enhancement and sustainment of K48- and K63-linked ubiquitin chains at these sites. This step is required for timely recruitment of the RAP80 and BRCA1 proteins and proper organization of RAP80- and BRCA1-associated protein complexes at DSB sites. This pathway is essential for optimal end resection at DSBs, and its abrogation leads to upregulation of the highly mutagenic alternative end-joining repair at the expense of error-free homologous recombination repair. Our data uncover a critical regulatory level in the DSB response and underscore the importance of fine-tuning the complex DDR network for accurate and balanced execution of DSB repair.

Targeting the centriolar replication factor STIL synergizes with DNA damaging agents for treatment of ovarian cancer

Advanced ovarian cancer is an incurable disease. Thus, novel therapies are required. We wished to identify new therapeutic targets for ovarian cancer. ShRNA screen performed in 42 ovarian cancer cell lines identified the centriolar replication factor STIL as an essential gene for ovarian cancer cells. This was verified in-vivo in orthotopic human ovarian cancer mouse models. STIL depletion by administration of siRNA in neutral liposomes resulted in robust anti-tumor effect that was further enhanced in combination with cisplatin. Consistent with this finding, STIL depletion enhanced the extent of DNA double strand breaks caused by DNA damaging agents. This was associated with centrosomal depletion, ongoing genomic instability and enhanced formation of micronuclei. Interestingly, the ongoing DNA damage was not associated with reduced DNA repair. Indeed, we observed that depletion of STIL enhanced canonical homologous recombination repair and increased BRCA1 and RAD51 foci in response to DNA double strand breaks. Thus, inhibition of STIL significantly enhances the efficacy of DNA damaging chemotherapeutic drugs in treatment of ovarian cancer.

Involvement of the nuclear proteasome activator PA28γ in the cellular response to DNA double-strand breaks

The DNA damage response (DDR) is a complex signaling network that leads to damage repair while modulating numerous cellular processes. DNA double-strand breaks (DSBs), a highly cytotoxic DNA lesion, activate this system most vigorously. The DSB response network is orchestrated by the ATM protein kinase, which phosphorylates key players in its various branches. Proteasome-mediated protein degradation plays an important role in the proteome dynamics following DNA damage induction. Here, we identify the nuclear proteasome activator PA28γ (REGγ; PSME3) as a novel DDR player. PA28γ depletion leads to cellular radiomimetic sensitivity and a marked delay in DSB repair. Specifically, PA28γ deficiency abrogates the balance between the two major DSB repair pathways--nonhomologous end-joining and homologous recombination repair. Furthermore, PA28γ is found to be an ATM target, being recruited to the DNA damage sites and required for rapid accumulation of proteasomes at these sites. Our data reveal a novel ATM-PA28γ-proteasome axis of the DDR that is required for timely coordination of DSB repair.