Predictive Biomarkers Of Response Research Articles

Low CD86 expression is a predictive biomarker for clinical response to the therapeutic HPV vaccine, IGMKK16E7: Results of a post-hoc analysis

Abstract Background Although therapeutic HPV vaccines could offer a non-invasive treatment for patients with cervical intraepithelial neoplasia (CIN), none have been clinically implemented. Oral administration of the therapeutic HPV vaccine, IGMKK16E7, results in the histological regression of HPV16-positive CIN2/3 to normal (complete response: CR). Here, we investigated biomarkers that could predict CR after oral administration of IGMKK16E7. Methods Forty-two patients administered with high-dose oral IGMKK16E7 in a Phase I/II trial were included. Cervical-exfoliated cells were collected before administration. Gene expression of CD4, CD8, Foxp3, PD-1, CTLA-4, CD103, CD28, CD80, CD86, and PD-L1 in the cells were measured by quantitative RT-PCR. ROC curve analysis and Mann-Whitney tests were used to explore potential biomarkers. Pearson correlation coefficient analysis was used to correlate gene expression profiles with clinical outcome. Results The only predictive biomarker of vaccine response for which ROC curve analysis showed significant diagnostic performance with histological CR was CD86 (AUC 0.71, 95%XI 0.53-0.88, p = .020). CR patients had significantly lower CD86 expression (CD86-low) than non-CR patients (p = .035). The CR rate for CD86-low and CD86-high cases was 50% and 19%, respectively, and CD86-low cases had a significantly higher CR rate (p = .047). Compared to all patients, the CD86-low group had a 1.5-fold increase in CR rate. Gene expression of CD86 and CTLA-4 showed the strongest positive correlation with clinical outcomes in the non-CR group (p < .001). Conclusion Low expression of CD86 in exfoliated cervical cells can be used as a pre-treatment biomarker to predict histological CR after IGMKK16E7 use.

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling. Methods A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence. Results Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype. Conclusions In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

Impact of oxaliplatin and trastuzumab combination therapy on tumor markers and T lymphocyte subsets for advanced gastric cancer

BACKGROUND Advanced gastric cancer (AGC) remains a challenging malignancy with poor prognosis. The combination of oxaliplatin and trastuzumab has shown promising results in AGC treatment. This study aimed to investigate the effects of oxaliplatin and trastuzumab combination therapy on serum tumor markers and T lymphocyte subsets in patients with AGC and to explore their potential as predictive biomarkers for treatment response. AIM To investigate the impact of oxaliplatin and trastuzumab combination therapy on serum markers and T cell subsets in patients with AGC. METHODS This prospective study enrolled 60 patients with AGC. All patients received oxaliplatin (130 mg/m2, every 3 weeks) and trastuzumab (8 mg/kg loading dose, followed by 6 mg/kg every 3 weeks) for six cycles. Serum carcinoembryonic antigen (CEA), cancer antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4) were measured before and after treatment. T-lymphocyte subsets, including CD3+, CD4+, CD8+, and CD4+ /CD8+ ratios, were also evaluated. The clinical response was assessed using the Response Evaluation Criteria in Solid Tumors version 1.1. RESULTS After six cycles of treatment, the CEA, CA19-9, and CA72-4 serum levels significantly decreased compared to baseline levels (P < 0.001). The percentages of CD3+ and CD4+ T lymphocytes increased significantly (P < 0.05), whereas the percentage of CD8+ T lymphocytes decreased (P < 0.05). The CD4+/CD8+ ratio also significantly increased after treatment (P < 0.05). Patients with a higher decrease in serum tumor markers (≥ 50% reduction) and a higher increase in CD4+/CD8+ ratio (≥ 1.5-fold) showed better clinical response rates (P < 0.05). CONCLUSION Oxaliplatin and trastuzumab combination therapy effectively reduced serum tumor marker levels and modulated T lymphocyte subsets in patients with AGC. Combination therapy not only has a direct antitumor effect, but also enhances the immune response in patients with AGC. Serum tumor markers and T lymphocyte subsets may serve as potential predictive biomarkers for treatment response in patients with AGC receiving combination therapy.

Tumorspheres as In Vitro Model for Identifying Predictive Chemoresistance and Tumor Aggressiveness Biomarkers in Breast and Colorectal Cancer

Chemoresistance remains a major challenge in the treatment of breast and colorectal cancer. For this reason, finding reliable predictive biomarkers of response to chemotherapy has become a significant research focus in recent years. However, validating in vitro results may be problematic due to the outcome heterogeneity. In this study, we evaluate the use of tumorspheres as an in vitro model for validating biomarkers of chemoresistance in breast and colorectal cancer. Our investigation highlights the crucial role of inflammation-related pathways in modulating the response to chemotherapy. Using in silico approaches, we identified specific markers elevated in responders versus non-responders patients. These markers were consistently higher in three-dimensional (3D) tumorsphere models compared to traditional adherent cell culture models. Furthermore, the number of tumorspheres from breast and colorectal cancer cells increased in response to cisplatin and oxaliplatin treatment, respectively, whereas cell viability decreased in adherent cell culture. This differential response underscores the importance of the 3D tumorsphere model in mimicking the tumor microenvironment more accurately than adherent cell culture. The enhanced chemoresistance observed in the 3D tumorspheres model and their correlation of data with the in silico study suggest that 3D culture models are a better option to approach the in vivo model and also to validate in silico data. Our findings indicate that tumorspheres are an ideal model for validating chemoresistance biomarkers and exploring the interplay between inflammation and chemoresistance in breast and colon cancer.

GOLM1 dictates acquired Lenvatinib resistance by a GOLM1-CSN5 positive feedback loop upon EGFR signaling activation in hepatocellular carcinoma.

Lenvatinib is a multiple receptor tyrosine kinases inhibitor (TKI) authorized for first-line treatment of hepatocellular carcinoma (HCC). However, Lenvatinib resistance is common in HCC clinical treatment, highlighting the urgent need to understand mechanisms of resistance. Here, we identified Golgi membrane protein 1 (GOLM1), a type II transmembrane protein originally located in the Golgi apparatus, as a novel regulator of Lenvatinib resistance. We found GOLM1 was overexpressed in Lenvatinib resistant human HCC cell lines, blood and HCC samples. Additionally, GOLM1 overexpression contributes to Lenvatinib resistance and HCC progression in vitro and in vivo. Mechanistically, GOLM1 upregulates CSN5 expression through EGFR-STAT3 pathway. Reversely, CSN5 deubiquitinates and stabilizes GOLM1 protein by inhibiting ubiquitin-proteasome pathway of GOLM1. Furthermore, clinical specimens of HCC showed a positive correlation between the activation of the GOLM1-EGFR-STAT3-CSN5 axis. Finally, GOLM1 knockdown was found to act in synergy with Lenvatinib in subcutaneous and orthotopic mouse model. Overall, these findings identify a mechanism of resistance to Lenvatinib treatment for HCC, highlight an effective predictive biomarker of Lenvatinib response in HCC and show that targeting GOLM1 may improve the clinical benefit of Lenvatinib.

Insights into multidrug resistance mechanisms: Exploring distinct miRNAs as prospective therapeutic agents in triple negative breast cancer

Triple Negative Breast Cancer (TNBC) constitutes 12–17 % of breast cancers and is distinguished by the absence of hormone receptor expression, deviating from other breast cancer types. Coupled with its elevated proliferation index, TNBC develops multidrug resistance, diminishing treatment efficacy, weakening disease prognosis, and leading to an aggressive clinical course. This study aimed to assess ABCB1, ABCC1, ABCG2, and ABCC9 gene expression, which play a primary role in the development of multidrug resistance, alongside miRNAs (miR-466, miR-4539, miR-659-3p, miR-3123, miR-3133, and miR-655-3p) targeting these genes. While ABCB1 (p = 0.433), ABCC1 (p < 0.05), and ABCG2 (p < 0.05) exhibited increased expression in tumor tissues, ABCC9 (p = 0.587) did not. miR-466 (p = 0.802), miR-4539 (p = 0.732), miR-659-3p (p = 0.807), and miR-3123 (p = 0.980) were upregulated, whereas miR-3133 (p < 0.05) and miR-655-3p (p = 0.190) were downregulated. Within the scope of our study, we also evaluated the clinical parameters like tumor size, stage, and neoadjuvant treatment that significantly impacted Progression Free Survival (PFS) and Overall Survival (OS). Considering these results, we found that the metastatic status significantly influenced PFS and OS. Chemotherapeutics were found to not affect survival times. Assessing the impact of miRNAs, which we view as potential therapeutic targets, on average survival revealed that elevated miR-3133 expression was correlated with shorter PFS and OS, whereas decreased miR-655-3p expression was associated with longer PFS and OS. In summary, the relevant miRNAs could serve as predictive biomarkers for drug response and aid in developing miRNA-targeted gene therapy strategies.

Role of Fyn expression in predicting the sensitivity to platinum‑based chemotherapy in patients with ovarian serous carcinoma.

Ovarian serous carcinoma is a gynecological malignancy associated with a high mortality rate, which is commonly diagnosed in the first instance at a late stage and has a propensity to develop resistance to platinum-based chemotherapy. Identifying reliable biomarkers for platinum sensitivity is critical for improving patient outcomes. The present retrospective study included 64 patients with high-grade serous ovarian carcinoma (Federation of Gynecology and Obstetrics stages III or IV). Patients were classified as platinum-sensitive (no relapse within 6 months of the last platinum administration) or platinum-resistant (relapse within 6 months). Immunohistochemical analysis was performed to evaluate Fyn expression in tumor tissues, and Fyn knockdown experiments were performed using the OVSAHO ovarian cancer cell line to assess carboplatin sensitivity. Fyn expression was significantly higher in platinum-resistant patients compared with in platinum-sensitive patients (P<0.01). A weighted Fyn expression score was developed and a cutoff score of 6 was determined to predict platinum sensitivity with a specificity of 65.5% and a sensitivity of 62.9%. Patients with low Fyn expression (score ≤6) exhibited higher platinum sensitivity and longer overall survival (P<0.05). Multivariate analysis identified Fyn expression and postoperative residual tumor size as independent predictors of platinum sensitivity (P=0.033 and P=0.023, respectively). In vitro, Fyn knockdown significantly increased carboplatin sensitivity in ovarian cancer cells (P<0.05). Fyn, a member of the Src family of kinases, serves a crucial role in various cellular functions and has been implicated in chemotherapy resistance. The results demonstrated a notable association between Fyn expression and platinum sensitivity in ovarian serous carcinoma. The findings suggested that Fyn may serve as a predictive biomarker for response to platinum-based chemotherapy, offering the potential for more personalized treatment strategies. To the best of our knowledge, the present study is the first to establish an association between Fyn expression and platinum sensitivity in advanced ovarian serous carcinoma. Prospective studies with larger, multi-center cohorts and comprehensive biomarker analyses are recommended to validate and extend these results, ultimately improving therapeutic strategies and patient prognosis.

1821MO Predictive biomarkers of dyspnea response to dexamethasone in cancer patients: A secondary analysis of the Alleviating Breathlessness in Cancer Patients with Dyspnea (ABCD) trial

1821MO Predictive biomarkers of dyspnea response to dexamethasone in cancer patients: A secondary analysis of the Alleviating Breathlessness in Cancer Patients with Dyspnea (ABCD) trial

797. A COMPARATIVE ANALYSIS ON THE EFFECTIVENESS OF DIFFERENT TREATMENT MODALITIES FOR ESOPHAGEAL CARCINOMA; A SYSTEMATIC REVIEW

Abstract Background Esophageal carcinoma; sixth most common cancer worldwide, presents a significant clinical challenge due to its aggressive nature and often late-stage diagnosis, resulting in poor prognosis and limited treatment options. Various treatment modalities, including surgery, chemotherapy, radiation therapy, immunotherapy, and targeted therapy, are utilized in clinical practice. However, the optimal treatment strategy remains uncertain, as the comparative effectiveness of these modalities is not well-defined. Past studies have provided conflicting evidence, necessitating a comprehensive evaluation to guide clinical decision-making. Therefore, this systematic review aims to compare the efficacy and safety of different treatment modalities for esophageal carcinoma, with the objective of informing evidence-based treatment approaches and improving patient outcomes. Methods Total 350 publications from PubMed, EMBASE, Cochrane, Google Scholar and Semantic Scholar databases were identified on the effectiveness of different treatment modalities for esophageal carcinoma between 2000 and 2024. Following deduplication, two independent reviewers initially screened the articles for eligibility with titles and abstracts, and then, with complete articles. Bias assessment using GRADE guidelines for observational studies was done. Non-English studies, case-series/case-reports/essays/book-chapters/conference-abstracts/editorials/thesis/dissertations and studies without full-texts were excluded. Results Overall, the effectiveness of each treatment modality for esophageal carcinoma depends on various factors, including tumor stage, histology, patient characteristics, and treatment regimen. Combination approaches, such as chemoradiotherapy or multimodal therapy, are often used to maximize treatment efficacy and improve patient outcomes. Conclusion Multidisciplinary collaboration, personalized treatment approach, integration of novel therapies, such as immunotherapy and targeted therapy, into standard treatment regimens, survivorship care and advocate for further research to identify optimal treatment sequencing, identify predictive biomarkers of treatment response, and explore novel therapeutic targets to improve outcomes for patients with esophageal carcinoma is recommended.

53197 Predictive biomarkers for response to omalizumab in patients with chronic spontaneous urticaria

53197 Predictive biomarkers for response to omalizumab in patients with chronic spontaneous urticaria

Metabolomic characterization of human glioblastomas and patient plasma: a pilot study

Background Glioblastoma (GBM) is a clinically challenging primary brain tumor with poor survival outcome despite surgical resection and intensive chemoradiation. The metabolic heterogeneity of GBM can become biomarkers for treatment response, resistance, and outcome prediction. The aim of the study is to investigate metabolic distinctions between primary and recurrent GBM tissue and patient plasma to establish feasibility for metabolic profiling. Methods A single-center cohort study analyzed tissue and blood samples from 15 patients with GBM using untargeted metabolomic/lipidomic assays. Metabolomic, lipidomic, and biogenic amine analyses were conducted on GBM tissue and patient plasma at diagnosis and recurrence using untargeted mass spectrometry. The study utilized a small but longitudinally collected cohort to evaluate alteration in metabolites, lipids, and biogenic amines between specimens at diagnosis and recurrence. Results Exploratory analysis revealed significant alteration in metabolites, lipids, and biogenic amines between diagnostic and recurrent states in both tumor and plasma specimens. Notable metabolites differed at recurrence, including N-alpha-methylhistamine, glycerol-3-phosphate, phosphocholine, and succinic acid in tissue, and indole-3-acetate, and urea in plasma. Principal component analysis revealed distinct metabolomic profiles between tumor tissue and patient plasma. Distinct metabolic profiles were observed in GBM tissue and patient plasma at recurrence, demonstrating the feasibility of using metabolomic methodologies for longitudinal studies. One patient exhibited a unique tumor resistance signature at diagnosis, possibly indicating a high-risk metabolomic phenotype. Conclusions In this small cohort, the findings suggest the potential of metabolomic signatures of GBM tissue and patient plasma for risk stratification, outcome prediction, and the development of novel adjuvant metabolic-targeting therapies. The findings suggest metabolic discrepancies at diagnosis and recurrence in tissue and plasma, highlighting potential implications for evaluation of clinical response. The identification of significant changes in metabolite abundance emphasizes the need for larger studies using targeted metabolomics to validate and further explore these profiles.

Predictive biomarkers of response to tocilizumab in giant cell arteritis (GCA): correlations with imaging activity.

In the recent EULAR recommendations, ultrasound examination is now recommended as a first-line imaging test in all patients with suspected giant cell arteritis (GCA) and the axillary arteries should be included in the standard exam. As an alternative to ultrasound evaluation, cranial and extracranial arteries can be examined using FDG-PET or MRI. The aim of our study was to observe in a retrospective case series whether there is a correlation between biomarkers and imaging activity in a population of patients followed in real life with GCA treated with prednisone (PDN) and tocilizumab (TCZ). We retrospectively enrolled 68 patients with newly diagnosed GCA between January 2020 and September 2021, followed in real life, who were examined at the Rheumatology Unit of the San Giovanni di Dio Hospital, Florence, Italy. Patients were evaluated at T0-T3-T6-T12-T18-T24 for the following blood tests: ESR, CRP, fibrinogen, platelet count, serum amyloid A (SAA), IL-6, and circulating calprotectin (MRP). Ultrasound examination of the temporal arteries and axillary arteries was assessed at T0 within 7days of starting treatment with high-dose glucocorticoids and subsequently at T3-T6-T12-T18-T24. A scale from 0 to 3 with semi-quantitative tools (SUV max) was assessed at T0-T12-T24. The evaluation of the correlation coefficient between laboratory and imaging variables has shown that SAA and MRP have the most powerful correlation with the PET score (0.523 and 0.64), and MRP also has an excellent correlation coefficient with the Halo score (0.658). The evaluation of the ROC curves shows for a PET score 3 and SAA values higher than 26mg/L, sensitivity of 81.5% and specificity of 84.1%, and for a PET score 3 and MRP values higher than 2.3 mcg/mL, sensitivity of 100% and specificity of 76.8%. In this study, we demonstrated that SAA and MRP can be useful as promising tools to detect GCA activity. The study demonstrates a good correlation between the two biomarkers and the imaging activity evaluated by the Halo and PET scores.

Comprehensive pan-cancer analysis reveals EPHB2 is a novel predictive biomarker for prognosis and immunotherapy response

PurposeRecent studies have increasingly linked Ephrin receptor B2 (EPHB2) to cancer progression. However, comprehensive investigations into the immunological roles and prognostic significance of EPHB2 across various cancers remain lacking.MethodsWe employed various databases and bioinformatics tools to investigate the impact of EPHB2 on prognosis, immune infiltration, genome instability, and response to immunotherapy. Validation of the correlation between EPHB2 expression and M2 macrophages included analyses using bulk and single-cell transcriptomic datasets, spatial transcriptomics, and multi-fluorescence staining. Moreover, we performed cMap web tool to screen for EPHB2-targeted compounds and assessed their potential through molecular docking and dynamics simulations. Additionally, in vitro validation using lung adenocarcinoma (LUAD) cell lines was conducted to confirm the bioinformatics predictions about EPHB2.ResultsEPHB2 dysregulation was observed across multiple cancer types, where it demonstrated significant diagnostic and prognostic value. Gene Set Enrichment Analysis (GSEA) indicated that EPHB2 is involved in enhancing cellular proliferation, invasiveness of cancer cells, and modulation of the anti-cancer immune response. Furthermore, it is emerged as a pan-cancer marker for M2 macrophage infiltration, supported by integrated analyses of transcriptomics and multiple fluorescence staining. In LUAD cells, knockdown of EPHB2 expression led to a decrease in both cell proliferation and migratory activity.ConclusionEPHB2 expression may serve as a pivotal indicator of M2 macrophage infiltration, offering vital insights into tumor dynamics and progression across various cancers, including lung adenocarcinoma, highlighting its significant prognostic and therapeutic potential for further exploration.

Unlocking the Potential: Epstein-Barr Virus (EBV) in Gastric Cancer and Future Treatment Prospects, a Literature Review

Gastric cancer (GC) is a complex disease with various etiologies. While Helicobacter pylori infection is still one of the leading risk factors for GC, increasing evidence suggests a link between GC and other infective agents such as Epstein Bar Virus (EBV). EBV-associated gastric cancer (EBVaGC) is now recognized as a distinct subgroup of GC, and the complex interactions between the virus and gastric mucosa may influence its development. A recent integrative analysis of the genome and proteome of GC tissues by The Cancer Genome Atlas project has identified EBVaGC as a specific subtype characterized by PIK3CA and ARID1A mutations, extensive DNA hyper-methylation, and activation of immune signaling pathways. These molecular characteristics are markers of the unique molecular profile of this subset of GC and are potential targets for therapy. This review aims to provide an overview of the current knowledge on EBVaGC. It will focus on the epidemiology, clinic-pathological features, and genetic characteristics of EBVaGC. Additionally, it will discuss recent data indicating the potential use of EBV infection as a predictive biomarker of response to chemotherapy and immune checkpoint inhibitors. The review also delves into potential therapeutic approaches for EBVaGC, including targeted therapies and adoptive immunotherapy, highlighting the promising potential of EBV as a therapeutic target.

Tumour mutational burden: clinical utility, challenges and emerging improvements.

Tumour mutational burden (TMB), defined as the total number of somatic non-synonymous mutations present within the cancer genome, varies across and within cancer types. A first wave of retrospective and prospective research identified TMB as a predictive biomarker of response to immune-checkpoint inhibitors and culminated in the disease-agnostic approval of pembrolizumab for patients with TMB-high tumours based on data from the Keynote-158 trial. Although the applicability of outcomes from this trial to all cancer types and the optimal thresholds for TMB are yet to be ascertained, research into TMB is advancing along three principal avenues: enhancement of TMB assessments through rigorous quality control measures within the laboratory process, including the mitigation of confounding factors such as limited panel scope and low tumour purity; refinement of the traditional TMB framework through the incorporation of innovative concepts such as clonal, persistentor HLA-corrected TMB, tumour neoantigen load and mutational signatures; and integration of TMB with established and emerging biomarkers such as PD-L1 expression, microsatellite instability, immune gene expression profiles and the tumour immune contexture. Given its pivotal functions in both the pathogenesis of cancer and the ability of the immune system to recognize tumours, a profound comprehension of the foundational principles and the continued evolution of TMB are of paramount relevance for the field of oncology.

Stearoyl-CoA desaturase inhibition is toxic to acute myeloid leukemia displaying high levels of the de novo fatty acid biosynthesis and desaturation.

Identification of specific and therapeutically actionable vulnerabilities, ideally present across multiple mutational backgrounds, is needed to improve acute myeloid leukemia (AML) patients' outcomes. We identify stearoyl-CoA desaturase (SCD), the key enzyme in fatty acid (FA) desaturation, as prognostic of patients' outcomes and, using the clinical-grade inhibitor SSI-4, show that SCD inhibition (SCDi) is a therapeutic vulnerability across multiple AML models in vitro and in vivo. Multiomic analysis demonstrates that SCDi causes lipotoxicity, which induces AML cell death via pleiotropic effects. Sensitivity to SCDi correlates with AML dependency on FA desaturation regardless of mutational profile and is modulated by FA biosynthesis activity. Finally, we show that lipotoxicity increases chemotherapy-induced DNA damage and standard chemotherapy further sensitizes AML cells to SCDi. Our work supports developing FA desaturase inhibitors in AML while stressing the importance of identifying predictive biomarkers of response and biologically validated combination therapies to realize their full therapeutic potential.

Construction of a prognostic model for colon cancer by combining endoplasmic reticulum stress responsive genes

Endoplasmic reticulum stress may affect the occurrence and development of cancer. However, its effect on the prognosis of colon cancer (CC) patients is not clear yet. Herein, based on TCGA database, we screened 15 endoplasmic reticulum stress responsive genes (ERSRGs) associated with the prognosis of CC patients by Cox regression. By LASSO and multivariate Cox regression analyses, a prognostic risk assessment model involving 12 genes (DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, GRIN2B, LRRC59, and RORC) was built. The survival curves indicated that patients in the low-risk group had good prognosis. ROC curves demonstrated a good performance of this 12-gene prognostic model, and the Riskscore could be considered as an independent prognostic factor. Patients in low-risk group benefit more from immune checkpoint inhibitor and immune checkpoint blockade (ICB) treatment. Besides, the enrichment analysis suggested a remarkable difference in Ca2+ signaling in both groups. Finally, based on the cMAP database, we identified several potential drugs that could target high-risk groups, such as Dasatinib, GNF-2, Saracatinib, and WZ-1-84. To sum up, our research constructed an ERSRGs-characteristic prognostic model. The model is a promising biomarker for prediction of clinical outcomes and immune therapy response of CC patients. SignificanceBased on the transcriptomic data of colon cancer in the TCGA database, this study screens 12 endoplasmic reticulum stress-related genes (ERSRGs), including DNAJB2, EIF4A1, YPEL4, COQ10A, IRX3, ASPHD1, NTRK2, TRIM39, XBP1, asphD1, NTRK2. GRIN2B, LRRC59, and RORC, and a prognostic model was constructed. This model can be used as a predictor of prognosis and immunotherapy response in colon cancer patients. At the same time, model-based prediction of drugs can also be a potential option for colon cancer treatment in the future.

Serum CYFRA 21-1 and CK19-2G2 as Predictive Biomarkers of Response to Transarterial Chemoembolization in Hepatitis C–related Hepatocellular Carcinoma Among Egyptians: A Prospective Study

Serum CYFRA 21-1 and CK19-2G2 as Predictive Biomarkers of Response to Transarterial Chemoembolization in Hepatitis C–related Hepatocellular Carcinoma Among Egyptians: A Prospective Study

Could Flow Cytometry Provide New Prognostic Markers in Colorectal Cancer?

Background/Objectives: Colorectal cancer (CRC) is still accompanied by significant mortality, which poses the necessity of novel markers to predict treatment success and patient survival. This study aims to evaluate the prognostic and survival impact of flowytometry (FC) in CRC patients. Methods: In this prospective study, 106 surgically resectable CRC patients were included. Tissue specimens from tumor and normal mucosa were collected and analyzed by FC. DNA and tumor index were calculated. In a subgroup of 46 patients, the CD26 expression on tumor cells was estimated. These parameters were compared with patients' tumor characteristics as stage, histology data, responsiveness to treatment, metastasis/recurrence, and, finally, patients' survival to identify possible new biomarkers. Results: The overall survival and the disease-specific survival in our study group was 76% and 72%, respectively, during the 7-year follow up period. Diploid tumors had better median survival than the aneuploid ones. The DNA index had significant correlation to the tumor index and response to neoadjuvant treatment. Similarly, the tumor index was also significantly related to the response to neoadjuvant treatment. Patients with a higher tumor index had worst survival rates. Surprisingly, CD26 levels were not associated with any of the parameters examined and were negatively related to tumor stage and differentiation. Conclusions: FC is a rapid and reliable method of cell analysis. In CRC, it has been used for prognostic and diagnostic purposes. In this study, we have shown that DNA and tumor index could become predictive biomarkers of tumor response to neoadjuvant treatment and survival of resectable CRC patients.

Predictive and pharmacodynamic biomarkers for combination therapy in stage III-IV melanoma: A Simon phase II trial (NCT03999749).

222 Background: The evaluation of biomarkers that predict response and immune-related adverse events (irAEs) is crucial for optimizing melanoma treatment with Immune checkpoint inhibitors (ICIs). We report predictive and pharmacodynamic biomarkers for response and irAEs using high-dimensional flow cytometry in a phase II trial combining nivolumab (3 mg/kg), ipilimumab (1 mg/ml), and the IL-6 receptor inhibitor tocilizumab (4 mg/kg) in unresectable/advanced melanoma patients. Methods: We analyzed serum and blood from melanoma patients at baseline, weeks 7 and 37, categorized them by irAE severity and clinical response. Patients were categorized based on the severity of irAEs (grades 3-5) (TOX), the absence of toxicity or grades 1-2 irAE (NT), clinical benefit (CB), and non-clinical benefit (NCB). Immune monitoring regimen included ELISA for IL-6, gp130, IL-23, osteopontin, and Luminex oncological panel (LXSAHM-22). We employed multi-parametric flow cytometry panels to examine myeloid cells, cytotoxic T cells, and checkpoint protein expression on immune cells. We processed ~1 million PBMCs per sample using various antibodies, with data acquisition performed via Sony’s ID7000 cytometer. The data underwent quality control, normalization PBMCs per patient, concatenation, dimensionality reduction, and clustering in FlowJo. Results: Among the 70 patients administered treatment, we observed a best overall response rate of 57%. Grade 3-5 irAEs occurred in 22% of patients by week 24. Patients manifesting irAEs exhibited notably higher baseline Th17 cell counts (NT=181±18 vs. Tox=311±49, p&lt;0.01) and CD26+ Naive CD4 T-cell populations (NT=5838±801 vs. Tox=9632±1343, p&lt;0.04), suggesting their potential role as predictive markers for toxicity. Additionally, in vitro investigations led us to identify CD26 co-stimulation as a preliminary step in TH17 cell differentiation. Key pharmacodynamic markers included a significant elevation in Treg cells (NCB=1286±71 vs. CB=1492±95, p=0.02) and reduction in serum gp130 levels (NCB=104±5 vs. CB=83±5 ng/ml, p&lt;0.01) at week 7 in addition to IL-6 (NCB=7.5±1.5 vs. CB=4.6±1.1 pg/ml, p&lt;0.01) and osteopontin (NCB=95±15 vs. CB=25±3 ng/ml, p&lt;0.01) by week 37 when compared to baseline. Conclusions: Our findings suggest that Th17 cells can serve as a toxicity biomarker for combination therapy with ipilimumab, nivolumab and tocilizumab. Circulating Treg cells and serum osteopontin have emerged as promising pharmacodynamic biomarkers. Clinical trial information: NCT03999749 .