Peripheral Blood Biomarkers Research Articles

CT-195 Predictive Value of ST2, REG3a, and MAGIC Algorithm in Haploidentical Transplantation With Post-Transplant Cyclophosphamide Outcomes

Recent studies have described protein biomarkers in peripheral blood associated to allogeneic-stem-cell transplantation (allo-SCT) outcomes. To date, two studies have focused on haploidentical allo-SCT with post-transplant cyclophosphamide (haplo-SCT-PTCy). These works evaluate ST2 and REG3α at days +15 and +30 but do not include the analysis of the MAGIC algorithm. Analyze ST2, REG3a, and MAGIC algorithm early weekly after haplo-SCT-PTCy and its association with transplant outcomes. Prospective study with 151 consecutive patients who underwent haplo-SCT-PTCy at University Hospital of Salamanca (2012-2020). Serial serum samples were collected on days 0, +3, +7, +14 and +21 in 81 patients. ST2 and REG3a serum concentration was established by Luminex XMap. Median luminescence levels between groups were compared using Wilcoxon-Mann-Whitney test. Cut-off points for each cytokine were estimated using Cutoff-Finder application in R. MAGIC algorithm was determined from the ST2 and REG3α values. Log-rank was used to compare survival curves. Multivariable analyses were carried out with Cox regression, including the most significant clinical variables. Recipient median age of 50 years, 73% of transplants were performed with reduced-intensity conditioning. Median follow-up of 35 months. Higher levels of ST2 were associated with higher NRM 1-year (0, +7, +14), lower OS 2-years (+7, +14), and GRFS 2-years (+14, +21). Higher levels of REG3α were associated with higher NRM 1-year (0, 7, 14, 21), lower OS 2-years (0, +7, +14, +21) and lower GRFS-2y (+14). Similarly, the analysis of MAGIC algorithm in univariate analysis distinguished two statistically significant risk groups for GRFS (+14), OS (0, +14), and NRM 1-year (0, +14). On multivariate analysis, OS was independently associated with HCT-CI ≥3, ST2 (0, +7, 14, +21), REG3α (0, +14, +21) and MAGIC (0, +14), NRM with ST2 (0, +14), REG3α (14) and HCT-CI ≥3. ST2 (+7, +14, +21) REG3α (+14), MAGIC (+14) and HCT-CI ≥3 were the only variables associated to GRFS. These results confirm the prognostic impact of ST2, REG3α in haplo-SCT-PTCy early on days +7 and +14 for OS, NRM and GRFS endpoints. Confirms the identification using the MAGIC algorithm of two risk groups in a homogeneous series of haplo-SCT-PTCy. Standardization in prospective and larger series is still required.

Absolute Lymphocyte Count Is an Independent Prognostic Factor for ER-positive HER2-negative Advanced Breast Cancer Patients Treated With CDK4/6 Inhibitors.

The aim of this study was to elucidate the clinical significance of peripheral blood biomarkers, including absolute lymphocyte count (ALC), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR) and C-reactive protein (CRP) in patients with estrogen receptor-positive human epidermal growth factor receptor 2-negative advanced breast cancer treated with the CDK4/6 inhibitors, abemaciclib and palbociclib. A total of 83 patients treated with fulvestrant plus abemaciclib or palbociclib were included in this study. Progression-free survival (PFS) and overall survival (OS) were compared in relation to baseline levels of ALC, NLR, PLR and CRP. The cut-off values of ALC, NLR, PLR, and CRP for PFS were determined from the receiver operating characteristic curve using the Youden index for area under the curve and set at 1,212/μl, 1.964, 170 and 0.220 mg/dl, respectively. In the abemaciclib-treated group, ALC-high patients showed significantly better PFS than ALC-low patients (p=0.0151) and multivariate analysis revealed that ALC was an independent prognostic factor for PFS (p=0.0085). In the palbociclib-treated group, there was no significant relationship between any peripheral blood biomarkers and PFS. In both treatment groups, ALC-high patients showed significantly better OS than ALC-low patients (p=0.0169 and 0.0290, respectively). Multivariate analysis revealed ALC was an independent prognostic factor for OS in both abemaciclib- and palbociclib-treated groups (p=0.0112 and 0.0202, respectively). ALC is an independent prognostic factor for estrogen receptor-positive human epidermal growth factor receptor 2-negative advanced breast cancer patients treated with the CDK4/6 inhibitors abemaciclib and palbociclib.

Ecotoxicological studies of surface and groundwater in the adjacent territories of the Shuakhevi HPP (Adjara AR)

In the pathogenesis of autoimmune diseases, including immune thrombocytopenia (ITP), maintenance of inflammation and the loss of immune tolerance is essential. Transforming growth factor-beta (TGF-β) is a regulatory cytokine with pleiotropic function. TGF-β inhibits differentiation of T helper (Th1, Th2) cells and promotes the development of peripheral Tregs. The aim of our study was to explore the plasma levels of TGF-β and to perform its correlative analyses with peripheral blood biomarkers of systemic inflammation (NLR, PLR, PMR, SII, dNLR) in patients with ITP who did not respond to the first line treatment and had splenectomy as a second line therapy. The concentrations of TGF-β in plasma was quantified using ELISA kits by eBioscience. Statistical analyses was performed using Graph Pad Prism - Mann Whitney U test; for the correlation analyses we used spearman rank correlation by SPSS program. Our study revealed that the level of TGF-β in patients with refractory ITP is significantly diminished compared to the healthy subjects or patients undergoing splenectomy for other reasons than autoimmune or malignant hematological pathologies. There was no correlation observed between the plasma concentrations of TGF-β and the peripheral blood biomarkers of systemic inflammation.

Utility of Differential White Cell Count and Cell Population Data for Ruling Out COVID-19 Infection in Patients With Community-Acquired Pneumonia

IntroductionThe main aim of this study was to assess the utility of differential white cell count and cell population data (CPD) for the detection of COVID-19 in patients admitted for community-acquired pneumonia (CAP) of different etiologies. MethodsThis was a multicenter, observational, prospective study of adults aged ≥18 years admitted to three teaching hospitals in Spain from November 2019 to November 2021 with a diagnosis of CAP. At baseline, a Sysmex XN-20 analyzer was used to obtain detailed information related to the activation status and functional activity of white cells. ResultsThe sample was split into derivation and validation cohorts of 1065 and 717 patients, respectively. In the derivation cohort, COVID-19 was confirmed in 791 patients and ruled out in 274 patients, with mean ages of 62.13 (14.37) and 65.42 (16.62) years, respectively (p<0.001). There were significant differences in all CPD parameters except MO-Y. The multivariate prediction model showed that lower NE-X, NE-WY, LY-Z, LY-WY, MO-WX, MO-WY, and MO-Z values and neutrophil-to-lymphocyte ratio were related to COVID-19 etiology with an AUC of 0.819 (0.790, 0.846). No significant differences were found comparing this model to another including biomarkers (p=0.18). ConclusionsAbnormalities in white blood cell morphology based on a few cell population data values as well as NLR were able to accurately identify COVID-19 etiology. Moreover, systemic inflammation biomarkers currently used were unable to improve the predictive ability. We conclude that new peripheral blood biomarkers can help determine the etiology of CAP fast and inexpensively.

Progress of advanced nanomaterials in diagnosis of neurodegenerative diseases

Neurodegenerative diseases (NDDs) encompass a wide range of clinically and pathologically diverse diseases characterized by progressive long-term cognitive decline, memory and function loss in daily life. Due to the lack of effective drugs and therapeutic strategies for preventing or delaying neurodegenerative progression, it is urgent to diagnose NDDs as early and accurately as possible. Nanomaterials, emerged as one of the most promising materials in the 21st century, have been widely applied and play a significant role in diagnosis and treatment of NDDs because of their remarkable properties including stability, prominent biocompatibility, unique structure, novel physical and chemical characteristics. In this review, we outlined general strategies for the application of different types of advanced materials in early and staged diagnosis of NDDs in vivo and in vitro. According to applied technology, in vivo research mainly involves magnetic resonance, fluorescence, and surface enhanced Raman imaging on structures of brain tissues, cerebral vessels and related distributions of biomarkers. In vitro research is focused on the detection of fluid biomarkers in cerebrospinal fluid and peripheral blood based on fluorescence, electrochemical, Raman and surface plasmon resonance techniques. Finally, we discussed the current challenges and future perspectives of biomarker-based NDDs diagnosis as well as potential applications regarding advanced nanomaterials.

Sleep Parameters and Plasma Biomarkers for Cognitive Impairment Evaluation in Patients With Cerebral Small Vessel Disease.

Cognitive impairment caused by cerebrovascular disease accounts for more than half of vascular dementia. However, neuropsychological tests are limited by their subjectivity. Additional effective approaches to evaluate cognitive impairment in patients with cerebrovascular disease are necessary. One hundred and thirty-two patients with cerebrovascular disease were recruited. One hundred participants met the criteria and completed neuropsychological scales. Sixty-nine participants proceeded with polysomnography, and 63 of them had their peripheral blood biomarkers measured. According to Mini-Mental State Examination scores, patients were divided into cognitively impaired and cognitively normal groups. The differences in biomarkers and sleep parameters between the groups were compared, and decision tree models were constructed to evaluate the evaluation ability of these indicators on cognitive decline. The integrated decision tree model of sleep parameters yielded an area under curve (AUC) of 0.952 (95% confidence interval [CI]: 0.911-0.993), while that of plasma biomarkers yielded an AUC of 0.872 (95% CI: 0.810-0.935) in the assessment of cognition status. Then the participants were automatically clustered into mild and severe cognitive impairment groups by multiple neuropsychological test results. The integrated plasma biomarker model showed an AUC of 0.928 (95% CI: 0.88-0.977), and the integrated sleep parameter model showed an AUC of 0.851 (95% CI: 0.783-0.919) in the assessment of mild/severe cognitive impairment. Integrated models which consist of sleep parameters and plasma biomarkers can accurately evaluate dementia status and cognitive impairment in patients with cerebral small vessel disease. This innovative study may facilitate drug development, early screening, clinical diagnosis, and prognosis evaluation of the disease.

Circulating Tumor and Immune Cells for Minimally Invasive Risk Stratification of Smoldering Multiple Myeloma.

Early intervention in smoldering multiple myeloma (SMM) requires optimal risk stratification to avoid under- and overtreatment. We hypothesized that replacing bone marrow (BM) plasma cells (PC) for circulating tumor cells (CTC), and adding immune biomarkers in peripheral blood (PB) for the identification of patients at risk of progression due to lost immune surveillance, could improve the International Myeloma Working Group 20/2/20 model. We report the outcomes of 150 patients with SMM enrolled in the iMMunocell study, in which serial assessment of tumor and immune cells in PB was performed every 6 months for a period of 3 years since enrollment. Patients with >0.015% versus ≤0.015% CTCs at baseline had a median time-to-progression of 17 months versus not reached (HR, 4.9; P<0.001). Presence of >20% BM PCs had no prognostic value in a multivariate analysis that included serum free light-chain ratio >20, >2 g/dL M-protein, and >0.015% CTCs. The 20/2/20 and 20/2/0.015 models yielded similar risk stratification (C-index of 0.76 and 0.78). The combination of the 20/2/0.015 model with an immune risk score based on the percentages of SLAN+ and SLAN- nonclassical monocytes, CD69+HLADR+ cytotoxic NK cells, and CD4+CXCR3+ stem central memory T cells, allowed patient' stratification into low, intermediate-low, intermediate-high, and high-risk disease with 0%, 20%, 39%, and 73% rates of progression at 2 years. This study showed that CTCs outperform BM PCs for assessing tumor burden. Additional analysis in larger series are needed to define a consensus cutoff of CTCs for minimally invasive stratification of SMM.

LBA74 Genomic biomarkers in peripheral blood (PB) from patients (pts) enrolled in the JAVELIN Bladder 100 trial of avelumab first-line (1L) maintenance in advanced urothelial carcinoma (aUC)

The relationship between blood biomarkers, tumor immunity, and benefit from immune checkpoint inhibitors (ICIs) is not well understood. The JAVELIN Bladder 100 trial (NCT02603432) demonstrated that avelumab 1L maintenance prolongs overall survival (OS) in pts with aUC that has not progressed with 1L chemotherapy. Blood biomarkers associated with tumor immune gene signatures in this trial may provide mechanistic insight into the development of antitumor immunity and indicate patient subpopulations that could benefit from ICIs.

The correlation between neutrophil-to-lymphocyte ratio, carcinoembryonic antigen, and carbohydrate antigen 153 levels with chemotherapy-related cognitive impairment in early-stage breast cancer patients.

BackgroundThe changes in inflammation and tumor biomarkers are associated with the anti-tumor immunological processes. Early detection and intervention are of great significance to the clinical management of cancer-related diseases. Peripheral blood biomarkers [e.g., neutrophil-to-lymphocyte ratio (NLR), carcinoembryonic antigen (CEA), and carbohydrate antigen 153 (CA153)] are obtained in real-timely, conveniently, and less invasively, and proved to availably predicted the disease states and prognosis of various cancers, including breast cancer (BC). Inflammation and poor disease management promote cognitive impairment. Chemotherapy-related cognitive impairment (CRCI) hazard long-term survival and quality of life (QOL) of BC patients, but its correlation with NLR, CEA, and CA153 is not clear.PurposeThis study aimed to investigate changes in NLR, CEA, and CA153 levels before and after chemotherapy and their correlation with CRCI in patients with early-stage BC.Materials and methodsThe 187 patients with BC who were measured for NLR, CEA, and CA153 values within the first 24 hours of admission, were assigned into two groups: the before/after chemotherapy group (BCG/ACG). The ACG was assigned into two subgroups based on the cognitive assessment results: the cognitive normal/impaired group (CNG/CIG). Patients’ self-perceived cognitive impairments were evaluated using a mini-mental state examination (MMSE), prospective and retrospective memory (PM and RM) questionnaire (PRMQ), and functional assessment of cancer therapy-cognitive function version 3 (FACT-Cog, version 3, including CogPCI, CogOth, CogPCA, and CogQOL). Their QOL was also evaluated.ResultsThe NLR and CA153 levels were elevated after chemotherapy (BCG vs ACG: Z = −1.996 and −1.615, P = 0.046 and 0.106, respectively), and significantly elevated in patients with CRCI (BCG vs CIG: Z = −2.444 and -2.293, P = 0.015 and 0.022; respectively). However, there was not reach significant difference in CEA levels between the four groups. In addition, there was a weak to moderate correlation between peripheral blood biomarkers (NLR, CEA, and CA153) levels and CRCI (r = −0.404, −0.205, −0.322; respectively; P < 0.001). Cognitive impairment scores (MMSE, PM, RM, and FACT-Cog) had a strong correlation with QOL in patients with early-stage BC (r = −0.786, 0.851, 0.849, and 0.938; respectively; P < 0.001).ConclusionNLR and CA153 m be valuable diagnostic adjuncts of CRCI, and CRCI has a strong correlation with QOL in patients with early-stage BC.

Machine learning model for the prediction of prostate cancer in patients with low prostate-specific antigen levels: A multicenter retrospective analysis.

ObjectiveThe aim of this study was to develop a predictive model to improve the accuracy of prostate cancer (PCa) detection in patients with prostate specific antigen (PSA) levels ≤20 ng/mL at the initial puncture biopsy.MethodsA total of 146 patients (46 with Pca, 31.5%) with PSA ≤20 ng/mL who had undergone transrectal ultrasound-guided 12+X prostate puncture biopsy with clear pathological results at the First Affiliated Hospital of Guangxi Medical University (November 2015 to December 2021) were retrospectively evaluated. The validation group was 116 patients drawn from Changhai Hospital(52 with Pca, 44.8%). Age, body mass index (BMI), serum PSA, PSA-derived indices, several peripheral blood biomarkers, and ultrasound findings were considered as predictive factors and were analyzed by logistic regression. Significant predictors (P < 0.05) were included in five machine learning algorithm models. The performance of the models was evaluated by receiver operating characteristic curves. Decision curve analysis (DCA) was performed to estimate the clinical utility of the models. Ten-fold cross-validation was applied in the training process.ResultsProstate-specific antigen density, alanine transaminase-to-aspartate transaminase ratio, BMI, and urine red blood cell levels were identified as independent predictors for the differential diagnosis of PCa according to multivariate logistic regression analysis. The RandomForest model exhibited the best predictive performance and had the highest net benefit when compared with the other algorithms, with an area under the curve of 0.871. In addition, DCA had the highest net benefit across the whole range of cut-off points examined.ConclusionThe RandomForest-based model generated showed good prediction ability for the risk of PCa. Thus, this model could help urologists in the treatment decision-making process.

MiR-3653-3P EXPRESSION IN PERIPHERAL BLOOD OF PATIENTS WITH OVARIAN CARCINOMA

Ovarian cancer is a late-stage cancer with early and frequent recurrence, and there is still no effective treatment.There are no sensitive and specific biomarkers to be used effectively in the early diagnosis and treatment of the disease.Those currently used in the clinic are extremely insufficient for the early diagnosis and treatment follow-up of the disease, in terms of accurately determining the minimal residual disease.Many studies have shown that deregulation or dysfunction of miRNAs in the small non-coding RNA class contributes to cancer development However, it is known that the expressions of a number of miRNAs differ in ovarian cancer. Examining the expression patterns of known miRNAs in cancer research by comparing them between patients and healthy people is extremely important in terms of finding disease-specific biological markers, and determining the roles of these molecules in the pathogenesis of ovarian cancer is also significant.In the thesis study presented, the expression profile of miR-3653-3p was investigated in a control group consisting of 150 high-risk ovarian cancer patients and 100 healthy individuals, and both groups were compared with each other.It was found that the expression level of miR-3653-3p in the peripheral blood of ovarian cancer patients was 9.49 times higher than the control groups and the results were shown to be statistically significant(p = 0.00).In addition to these results, whether miR-3653-3p can be used as a non-invasive biomarker in peripheral blood for ovarian cancer was evaluated by ROC analysis and it was shown that the molecule in question was a statistically significant biomarker.

Peripheral Blood Biomarkers Predictive of Efficacy Outcome and Immune-Related Adverse Events in Advanced Gastrointestinal Cancers Treated with Checkpoint Inhibitors.

Simple SummaryAlthough immune checkpoint inhibitors improve the survival of patients with advanced gastrointestinal cancers, they also cause a series of immune-related adverse events, which could sometimes be lethal and may hamper the effectiveness of anticancer therapies. The purpose of this study was to explore clinically accessible biomarkers to predict survival and adverse events in patients with advanced gastrointestinal cancers treated with checkpoint inhibitors. In a retrospective cohort containing 243 patients, we found that early treatment lines, the presence of immune-related adverse events, and a lower posttreatment neutrophil-to-lymphocyte ratio were independent factors predicting superior prognosis. Good physical strength and a low posttreatment neutrophil-to-lymphocyte ratio were independent risk factors for immune-related adverse events. These findings may assist in identifying patients who are more likely to respond to immunotherapy and suffer from fewer toxicities, which is of great value in guiding clinical decisions.Background: Gastrointestinal cancers constitute a major burden of global cancer mortalities. In recent years, the advent of immune checkpoint inhibitors has greatly improved the survival of patients with advanced gastrointestinal cancers, while predictive biomarkers of treatment efficacy and toxicities are still unmet demands. Methods: In our retrospective study, patients with advanced gastrointestinal cancers who received single or double immune checkpoint inhibitors in the Department of Gastrointestinal Oncology in Peking University Cancer Hospital between July 2016 and February 2022 were enrolled. Records of clinicopathological information, survival parameters, safety data, and baseline and posttreatment peripheral blood constituents were retrieved. Cox regression analysis and logistic regression analysis were performed to identify the predictive factors of treatment outcomes and immune-related adverse events. Results: We demonstrated that early treatment lines, the presence of immune-related adverse events, and a lower C2 neutrophil-to-lymphocyte ratio were independent factors predicting a superior objective response rate and progression-free survival in patients treated with immunotherapy. Lower ECOG PS, higher baseline albumin, and lower C2 neutrophil-to-lymphocyte ratios were independent risk factors for the onset of immune-related adverse events. Patients who succumbed to immune-related adverse events during immunotherapy presented better survival. Conclusion: Our results indicate that peripheral blood markers have potential for predicting treatment outcomes and immune-related adverse events in patients with advanced gastrointestinal cancer. Prospective validations are warranted.

Epitope Detection in Monocytes (EDIM) As a New Method of Liquid Biopsy in Pediatric Rhabdomyosarcoma.

Biomarkers allowing characterization of pediatric rhabdomyosarcoma (RMS) are lacking. Epitope detection in monocytes (EDIM) is a novel method focused on detection of the biomarkers TKTL1 (transketolase-like protein 1) and Apo10 (epitope of DNaseX) in activated monocytes (CD14+/CD16+) from patient’s blood. We investigated the expression of these biomarkers in RMS cell lines, tumor material, and peripheral blood from RMS patients. Expression levels of TKTL1 and DNaseX/Apo10 in RMS cell lines (RH30, RD) and tumor samples were analyzed by RT-PCR and flow cytometry. Blood samples of 29 RMS patients were measured and compared to 27 healthy individuals. The percentages of activated CD14+/CD16+ monocytes harboring TKTL1 and Apo10 were determined. EDIM-TKTL1 and EDIM-Apo10 expression scores were calculated. The relationship between TKTL1 expression and DNA-hypomethylation was evaluated. Both RMS cell lines and tumor samples showed significantly higher expression levels of TKTL1 and DNaseX/Apo10 compared to skeletal muscle cells (SkMC). EDIM-TKTL1 and EDIM-Apo10 scores were positive in 96.5% of patients with RMS. All healthy controls had negative corresponding scores. RMS cell lines show increased expression levels of the biomarkers TKTL1 and DNaseX/Apo10. The sensitivity of the EDIM blood test indicates that this assay might serve as an additional tool in pediatric RMS.

Dynamic changes in peripheral blood monocytes early after anti-PD-1 therapy predict clinical outcomes in hepatocellular carcinoma.

Immune checkpoint inhibitors are effective for advanced hepatocellular carcinoma (HCC), but there remains a need for peripheral blood biomarkers to predict the clinical response. Here, we analyzed the peripheral blood of 45 patients with advanced HCC who underwent nivolumab. During treatment, frequency of classical monocytes (CD14+CD16−) was increased on day 7, and the fold increase in the frequency on day 7 over day 0 (cMonocyteD7/D0) was significantly higher in patients with durable clinical benefit (DCB) than in patients with non-DCB (NDB). When we analyzed transcriptomes of classical monocytes, CD274, gene encoding PD-L1, was upregulated in NDB patients compared to DCB patients at day 7. Notably, gene signature of suppressive tumor-associated macrophages, or IL4l1+PD-L1+IDO1+ macrophages, was enriched after treatment in NDB patients, but not in DCB patients. Accordingly, the fold increase in the frequency of PD-L1+ classical monocytes at day 7 over day 0 (cMonocyte-PDL1D7/D0) was higher in NDB patients than DCB patients. The combined biomarker cMonocyteD7/D0/cMonocyte-PDL1D7/D0 was termed the “monocyte index”, which was significantly higher in DCB patients than NDB patients. Moreover, the monocyte index was an independent prognostic factor for survival. Overall, our results suggest that early changes of circulating classical monocytes, represented as a monocyte index, could predict clinical outcomes of advanced HCC patients undergoing anti-PD-1 therapy.Supplementary InformationThe online version contains supplementary material available at 10.1007/s00262-022-03258-6.

Multi-Omic Biomarkers for Patient Stratification in Sjogren's Syndrome-A Review of the Literature.

Sjögren’s syndrome (SS) is a heterogeneous autoimmune rheumatic disease (ARD) characterised by dryness due to the chronic lymphocytic infiltration of the exocrine glands. Patients can also present other extra glandular manifestations, such as arthritis, anaemia and fatigue or various types of organ involvement. Due to its heterogenicity, along with the lack of effective treatments, the diagnosis and management of this disease is challenging. The objective of this review is to summarize recent multi-omic publications aiming to identify biomarkers in tears, saliva and peripheral blood from SS patients that could be relevant for their better stratification aiming at improved treatment selection and hopefully better outcomes. We highlight the relevance of pro-inflammatory cytokines and interferon (IFN) as biomarkers identified in higher concentrations in serum, saliva and tears. Transcriptomic studies confirmed the upregulation of IFN and interleukin signalling in patients with SS, whereas immunophenotyping studies have shown dysregulation in the immune cell population frequencies, specifically CD4+and C8+T activated cells, and their correlations with clinical parameters, such as disease activity scores. Lastly, we discussed emerging findings derived from different omic technologies which can provide integrated knowledge about SS pathogenesis and facilitate personalised medicine approaches leading to better patient outcomes in the future.

The tissue-resident marker CD103 on peripheral blood T cells predicts responses to anti-PD-1 therapy in gastric cancer.

Immune checkpoint inhibitors (ICIs) have revolutionized cancer treatment. Since clinical benefits are limited to a subset of patients, we aimed to identify peripheral blood biomarkers that predict the efficacy of the anti-programmed cell death protein 1 (PD-1) antibody (nivolumab) in patients with gastric cancer. We collected peripheral blood samples from gastric cancer patients (n = 29) before and after treatment with nivolumab and investigated the relationship between the frequency of surface or intracellular markers among nivolumab-binding PD-1+CD8+ T cells and treatment responses using multicolor flow cytometry. The tumors, lymph nodes, and peripheral blood of gastric cancer patients who underwent gastrectomy following nivolumab treatment were collected, and nivolumab-binding PD-1+CD8+ T cells in these tissue samples were characterized. Patients with a high frequency of CD103 among PD-1+CD8+ T cells in peripheral blood 2weeks after the start of treatment had significantly better progression-free survival than the low group (P = 0.032). This CD103+PD-1+CD8+ T cell population mainly consisted of central memory T cells, showing the high expression of Ki-67 and few cytotoxic granules. In contrast, effector memory T cells were more frequently observed among CD103+PD-1+CD8+ T cells in tumors, which implied a change in the differentiated status of central memory T cells in lymph nodes and peripheral blood to effector memory T cells in tumors during the treatment with ICIs. A high frequency of CD103 among PD-1+CD8+ T cells 2weeks after nivolumab treatment in patients with advanced gastric cancer may be a useful biomarker for predicting the efficacy of anti-PD-1 therapy.

Behavioral- and blood-based biomarkers for Huntington's disease: Studies on the R6/1 mouse model with prospects for early diagnosis and monitoring of the disease

BackgroundHuntington's disease (HD) is a genetic neurodegenerative disorder characterized by a triad of cognitive, psychiatric and motor symptoms. One of the main mechanisms of the disease, besides the aggregation of mutant proteins, is the chronic inflammation that occurs in patients long before the onset of motor dysfunction. Currently, no effective therapy is available for HD. As the progression of HD is usually slow and its first clinical manifestations are non-specific, a correct diagnosis is difficult. Moreover, any attempts to develop therapies for HD require monitoring of unequivocal markers of the disease which are also hardly available. ObjectiveUsing a mouse model of HD, we aimed to determine a battery of biomarkers in peripheral blood, as well as those related to cognitive or anxiety disturbances, corresponding to the most characteristic breakpoints in HD. MethodsThe R6/1 mouse line was used as an animal HD model. Levels of cytokines and hormones in blood were estimated by ELISA. A series of behavioral and movement tests was applied. ResultsSignificant elevation of levels of specific inflammatory markers (IL-6, TNF-α, IL-1β, IL-12) was observed in the course of HD. At early stages of the disease, an impairment of anti-inflammatory defense mechanisms was evident, expressed by a significant decrease in IL-10 levels. The disturbances were faster in females than in males which might also translate into a potentially worse response to any administered drugs. Impaired memory and anxiety could be detected. ConclusionA set of simple behavioral- and blood-based biomarkers for HD has been detected.

P1210: IMMUNE CORRELATES OF RESPONSE TO GLOFITAMAB: BIOMARKER FINDINGS FROM A PIVOTAL PHASE II EXPANSION STUDY IN PATIENTS WITH RELAPSED OR REFRACTORY (R/R) DIFFUSE LARGE B-CELL LYMPHOMA (DLBCL)

Background: Glofitamab is a T-cell-engaging bispecific antibody with a novel 2:1 configuration that confers bivalency for CD20 (B cells) and monovalency for CD3 (T cells). In an ongoing Phase I/II study (NCT03075696), glofitamab demonstrated durable complete responses (CR) and a favorable safety profile in patients (pts) with R/R B-cell lymphomas (Phase I dose-escalation part; Hutchings, et al. 2021) and in pts with R/R DLBCL (pivotal Phase II expansion). Aims: To evaluate tumor and peripheral blood (PB) biomarkers associated with clinical response to glofitamab in the pivotal Phase II expansion. Methods: Pts with DLBCL (DLBCL, NOS, HGBCL, PMBCL, or trFL; n=107) and ≥2 prior therapies received intravenous (IV) obinutuzumab pretreatment (Gpt; 1000mg) 7 days before the first glofitamab dose. IV glofitamab was then given as step-up doses on Day (D) 1 (2.5mg) and D8 (10mg) of Cycle (C) 1 and at the target dose (30mg) on D1 of C2–12 (21-day cycles). Response was assessed by Independent Review Committee (Lugano 2014 criteria). All pts provided informed consent. Baseline (BL) tumor biopsies were assessed by CD20/PAX5 immunohistochemistry (n=64) and CD8/Ki67 immunofluorescence (IF) (n=61). PB biomarkers were evaluated by flow cytometry (n=87) and plasma cytokines by ELISA (n=70). Immune and stromal cell type were inferred from bulk tumor RNAseq samples (n=55) using xCell cell type enrichment analysis. All BL samples were collected prior to Gpt. Results: Analysis of BL tumor biopsies showed all pts were CD20 positive (range: ~35–98% CD20+ PAX5+ B cells) and CD20 levels were not associated with response. A trend towards higher CD8 counts was observed in pts with CR (by IF in total CD8 and CD8+Ki67- T cells). Gene expression analysis showed that responders had higher tumor microenvironment abundance enrichment scores, including higher CD4+ and CD8+ T-cell subsets scores (Figure). PB immune profiling revealed a positive association of BL counts of B cells (p<0.01), CD4 T cells (p=0.02), and CD4 effector memory (EM) cells (p=0.03) with response. There were no significant differences in BL counts of CD8 subsets, regulatory T cells, natural killer cells or monocytes. In pts with progressive disease (PD), there was a trend towards higher expression of the checkpoint marker PD1 on CD8 cells (p=0.05). Pts with CR had lower levels of IL-6 and C-reactive protein (CRP) at BL (test for association with CR: p=0.1 and p=0.01, respectively). Early on-treatment changes in PB were associated with response to glofitamab: induction of IL-6, IFNγ, IL-10, and TNFα in the 6 hours after the first glofitamab dose was strongest in pts with CR (IL-6, IFNγ, IL-10: 6- to 16-fold induction; TNFα: 1.5-fold induction). Transient margination of CD4 and CD8 T cells was strongest in pts with CR. Additional analyses, including ctDNA, are ongoing and updated data will be presented. Image:Summary/Conclusion: Biomarker results from the expansion cohort in pts with R/R DLBCL were consistent with those from the dose-escalation (Broeske et al. 2021), including comparable BL tumor CD20 expression across response categories, a trend towards higher BL tumor CD8 levels in pts with CR, and lower BL IL-6 and CRP in pts with CR. T-cell margination was strongest in pts with CR. Several novel response-associated biomarkers were identified in PB including higher BL B cell, CD4, and CD4 EM counts in responders and higher PD1 expression on CD8 in pts with PD. These data suggest a model where the clinical activity of glofitamab may be dependent upon immune contexture in the tumor and PB at the start of treatment.

Network-Based Analysis Reveals Novel Biomarkers in Peripheral Blood of Patients With Preeclampsia.

WGCNA is a potent systems biology approach that explains the connection of gene expression based on a microarray database, which facilitates the discovery of disease therapy targets or potential biomarkers. Preeclampsia is a kind of pregnancy-induced hypertension caused by complex factors. The disease’s pathophysiology, however, remains unknown. The focus of this research is to utilize WGCNA to identify susceptible modules and genes in the peripheral blood of preeclampsia patients. Obtain the whole gene expression data of GSE48424 preeclampsia patients and normal pregnant women from NCBI’s GEO database. WGCNA is used to construct a gene co-expression network by calculating correlation coefficients between modules and phenotypic traits, screening important modules, and filtering central genes. To identify hub genes, we performed functional enrichment analysis, pathway analysis, and protein-protein interaction (PPI) network construction on key genes in critical modules. Then, the genetic data file GSE149437 and clinical peripheral blood samples were used as a validation cohort to determine the diagnostic value of these key genes. Nine gene co-expression modules were constructed through WGCNA analysis. Among them, the blue module is significantly related to preeclampsia and is related to its clinical severity. Thirty genes have been discovered by using the intersection of the genes in the blue module and the DEGs genes as the hub genes. It was found that HDC, MS4A2, and SLC18A2 scored higher in the PPI network and were identified as hub genes. These three genes were also differentially expressed in peripheral blood validation samples. Based on the above three genes, we established the prediction model of peripheral blood markers of preeclampsia and drew the nomogram and calibration curve. The ROC curves were used in the training cohort GSE48424 and the validation cohort GSE149437 to verify the predictive value of the above model. Finally, it was confirmed in the collected clinical peripheral blood samples that MS4A2 was differentially expressed in the peripheral blood of early-onset and late-onset preeclampsia, which is of great significance. This study provides a new biomarker and prediction model for preeclampsia.

The Prognostic Capacity of Systemic Inflammation Response Index, Neutrophil-to-Lymphocyte Ratio, Lymphocyte-to-Monocyte Ratio, and Platelet-to-Lymphocyte Ratio in Patients with Hypopharyngeal Squamous Cell Carcinoma

Introduction: Systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) have been proposed as peripheral blood biomarkers. We compared these blood biomarkers to identify the best predictor in patients with hypopharyngeal squamous cell carcinoma (HPSCC). Methods: We conducted a retrospective study on 304 patients with HPSCC. SIRI was divided into three groups using X-tile version 3.6.1. The optimal cut-off points for NLR, LMR, and PLR were selected through RStudio. We compared the prognostic capacity of SIRI with that of NLR, LMR, and PLR using receiver operating characteristic curves. Results: Smoking, cancer in the postcricoid region, lymph node metastasis (N+), extracapsular invasion, SIRI in the highest tertile (>2.80), and LMR in the lowest tertile (<5.0) may cause poor 5-year overall survival (OS) in patients with HPSCC. Local and distant recurrences may occur earlier in those with lymph node metastasis and a tumor invading beyond the mucosa layer. Conclusions: SIRI was a better predictor of OS than LMR, PLR, and NLR in HPSCC patients. SIRI in the highest tertile (>2.80) and LMR in the lowest tertile (<5.0) may cause poor 5-year OS.