Disease Progression In Group Research Articles

Prognostic Nutrition Index as a Biomarker for Treatment Sensitivity to Chemotherapy and Nivolumab as the First-Line Treatment in Patients with Unresectable Advanced or Recurrent Gastric Cancer: A Multicenter Study

Introduction: This multicenter study aimed to determine whether the pretreatment prognostic nutrition index (PNI) or a change in the index after two treatment courses could be a biomarker for predicting treatment sensitivity in patients with unresectable advanced or recurrent gastric cancer (GC) treated using chemotherapy and nivolumab as the first-line treatment. Methods: This multicenter retrospective study with 104 patients was conducted at 12 institutions. PNI was calculated before treatment and after two courses of treatment in each case. We also focused on changes in PNI from the pretreatment value. Results: After two courses of chemotherapy plus nivolumab treatment, the high PNI group had significantly better rates of overall survival (OS) (p = 0.0016) and time to treatment failure (p = 0.0060). Low PNI was an independent prognostic factor predicting both therapeutic sensitivity to chemotherapy plus nivolumab treatment and poorer OS. Furthermore, correlation with low pretreatment PNI transitioning to high after two courses of treatment was not noted in any patient in the progressive disease group (p = 0.0075). Conclusions: PNI is a score composed of a patient’s albumin level and lymphocyte count that can be easily assessed in daily clinical practice. Evaluating it is easy for each treatment; thus, when there is a focus on its transition, PNI could be a very powerful biomarker for predicting treatment sensitivity.

The value of predicting neoadjuvant chemotherapy early efficacy in nasopharyngeal carcinoma based on amide proton transfer imaging and diffusion weighted imaging.

Early detection of nasopharyngeal carcinoma (NPC) patients who are not sensitive to neoadjuvant chemotherapy (NAC) can guard against overtreatment. This study aimed to evaluate the effectiveness of amide proton transfer (APT) imaging and diffusion-weighted imaging (DWI) in predicting the early response to NAC in patients with NPC. This prospective study enrolled fifty patients with biopsy-confirmed NPC from September 2021 to May 2023. Magnetic resonance imaging (MRI) including APT and DWI, was performed before NAC. After NAC, patients were divided into complete response (CR), partial response (PR), and stable disease (SD) and progressive disease (PD) groups based on the Response Evaluation Criteria in Solid Tumours Version 1.1. The Kruskal-Wallis H test was used for statistical analysis. The differences in APT and apparent diffusion coefficient (ADC) values among the different efficacy groups were compared, the receiver operating characteristic (ROC) curve was drawn for statistically significant parameters, and the area under the curve (AUC) was calculated. Fifty patients (mean age: 47±14 years; 42 males and 8 females) were included in the final analysis (11 were in the CR group, 30 in the PR group, 9 in the SD group, and 0 in the PD group). The ADC values showed no significant differences among the different treatment response groups. The SD group showed significantly lower APTmax (P=0.025), APTskewness (P=0.025) and APT90% (P=0.001) values than the CR and PR groups. Setting APT90% =3.10% as the cut-off value, optimal diagnostic performance (AUC: 0.831; sensitivity: 0.778; specificity: 0.878) was obtained in predicting the SD group. APT imaging can predict the early tumour response to NAC in patients with NPC. APT imaging may be superior to DWI in predicting tumour response.

Appearance of New Lesions Associate With Poor Prognosis in Pembrolizumab-Treated Urothelial Carcinoma

ObjectivesThis study investigated the variations in response patterns, including target lesion enlargement and the emergence of new lesions, in patients with urothelial carcinoma receiving pembrolizumab therapy and assessed the impact of new lesions on patient outcomes. MethodsThis retrospective analysis included patients with urothelial carcinoma treated with pembrolizumab following platinum failure. Response Evaluation Criteria in Solid Tumors criteria were used to assess the target lesion size and appearance of new lesions. Patients were categorized into 2 groups: the primary progressive disease (PD) group, consisting of patients who progressed within 28 to 84 days of treatment initiation, and the secondary PD group, consisting of patients who progressed more than 84 days after treatment initiation. Survival analyses were performed to evaluate the impact of new lesions on patient outcomes. ResultsIn this study, 42 patients experienced primary PD, and 37 experienced secondary PD. Among patients with primary PD, 64.3%, 73.8%, 45.2% had an increase of 20% or more in target lesion size, newly emerged lesions, and both an increase in target lesion size and new lesions, respectively. Kaplan–Meier analysis revealed that patients with primary PD and new lesions had significantly shorter overall survival after PD than those with only target lesion growth and those with secondary PD (both P < .001). ConclusionThis study revealed the heterogeneity of response patterns during pembrolizumab therapy in patients with urothelial carcinoma and primary pembrolizumab resistance and the presence of new lesions early in treatment. Earlier imaging evaluation should be performed to assess for the appearance of new lesions, leading to sequential treatment.

Quantitative SPECT/CT Metrics in Early Prediction of [177Lu]Lu-DOTATATE Treatment Response in Gastroenteropancreatic Neuroendocrine Tumor Patients.

Our objective is to explore quantitative imaging markers for early prediction of treatment response in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NETs) undergoing [177Lu]Lu-DOTATATE therapy. By doing so, we aim to enable timely switching to more effective therapies in order to prevent time-resource waste and minimize toxicities. Methods: Patients diagnosed with unresectable or metastatic, progressive, well-differentiated, receptor-positive GEP-NETs who received 4 sessions of [177Lu]Lu-DOTATATE were retrospectively selected. Using SPECT/CT images taken at the end of treatment sessions, we counted all visible tumors and measured their largest diameters to calculate the tumor burden score (TBS). Up to 4 target lesions were selected and semiautomatically segmented. Target lesion peak counts and spleen peak counts were measured, and normalized peak counts were calculated. Changes in TBS (ΔTBS) and changes in normalized peak count (ΔnPC) throughout treatment sessions in relation to the first treatment session were calculated. Treatment responses were evaluated using third-month CT and were binarized as progressive disease (PD) or non-PD. Results: Twenty-seven patients were included (7 PD, 20 non-PD). Significant differences were observed in ΔTBSsecond-first, ΔTBSthird-first, and ΔTBSfourth-first (where second-first, third-first, and fourth-first denote scan number between the second and first, third and first, and fourth and first [177Lu]Lu-DOTATATE treatment cycles), respectively) between the PD and non-PD groups (median, 0.043 vs. -0.049, 0.08 vs. -0.116, and 0.109 vs. -0.123 [P = 0.023, P = 0.002, and P < 0.001], respectively). ΔnPCsecond-first showed significant group differences (mean, -0.107 vs. -0.282; P = 0.033); ΔnPCthird-first and ΔnPCfourth-first did not reach statistical significance (mean, -0.122 vs. -0.312 and -0.183 vs. -0.405 [P = 0.117 and 0.067], respectively). At the optimal threshold, ΔTBSfourth-first exhibited an area under the curve (AUC) of 0.957, achieving 100% sensitivity and 80% specificity. ΔTBSsecond-first and ΔTBSthird-first reached AUCs of 0.793 and 0.893, sensitivities of 71.4%, and specificities of 85% and 95%, respectively. ΔnPCsecond-first, ΔnPCthird-first, and ΔnPCfourth-first showed AUCs of 0.764, 0.693, and 0.679; sensitivities of 71.4%, 71.4%, and 100%; and specificities of 75%, 70%, and 35%, respectively. Conclusion: ΔTBS and ΔnPC can predict [177Lu]Lu-DOTATATE response by the second treatment session.

Machine learning models for predicting of PD-1 treatment efficacy in Pan-cancer patients based on routine hematologic and biochemical parameters

Immune checkpoint blockade therapy targeting the programmed death-1(PD-1) pathway has shown remarkable efficacy and durable response in patients with various cancer types. Early prediction of therapeutic efficacy is important for optimizing treatment plans and avoiding potential side effects. In this work, we developed an efficient machine learning prediction method using routine hematologic and biochemical parameters to predict the efficacy of PD-1 combination treatment in Pan-Cancer patients. A total of 431 patients with nasopharyngeal carcinoma, esophageal cancer and lung cancer who underwent PD-1 checkpoint inhibitor combination therapy were included in this study. Patients were divided into two groups: progressive disease (PD) and disease control (DC) groups. Hematologic and biochemical parameters were collected before and at the third week of PD-1 therapy. Six machine learning models were developed and trained to predict the efficacy of PD-1 combination therapy at 8–12 weeks. Analysis of 57 blood biomarkers before and after three weeks of PD-1 combination therapy through statistical analysis, heatmaps, and principal component analysis did not accurately predict treatment outcome. However, with machine learning models, both the AdaBoost classifier and GBDT demonstrated high levels of prediction efficiency, with clinically acceptable AUC values exceeding 0.7. The AdaBoost classifier exhibited the highest performance among the 6 machine learning models, with a sensitivity of 0.85 and a specificity of 0.79. Our study demonstrated the potential of machine learning to predict the efficacy of PD-1 combination therapy based on changes in hematologic and biochemical parameters.

Progression-Free Survival and Treatment-Free Interval in Head and Neck Cancer with Long-Term Response to Nivolumab: Timing of Active Discontinuation.

The optimal timing for actively discontinuing immune checkpoint inhibitor therapy in long-term responders with recurrent/metastatic head and neck squamous cell carcinoma (R/M HNSCC) remains unresolved. We conducted a retrospective study of 246 patients with R/M HNSCC treated with nivolumab to determine the optimal timing to actively discontinue nivolumab therapy. We examined the point at which progression-free survival (PFS) plateaued in all cases. We compared the prognosis of 19 (7.7%) ongoing cases and 227 (92.3%) discontinued cases and analyzed treatment duration and treatment-free interval (TFI). The 6-year overall survival was 11.8% (median, 12.1), and the 6-year PFS was 15.3% (median, 3.0). The PFS curve remained stable for 3 years. The median duration of nivolumab treatment was 2.9 months (range 0.03-81.9): Ongoing group, 41.8 (5.6-81.9); Decision group, 36.8 (4.0-70.1); Toxicity group, 30.6 (2.8-64.8); and progressive disease group, 2.0 (0.03-42.9). TFI in the Decision group was 15.1 months (0.6-61.6) and 30.6 months (2.8-64.8) in the Toxicity group. Long-term responses in R/M HNSCC patients treated with nivolumab are rare but gradually increasing. For this patient group, our best estimate of the optimal time to end treatment is 3 years, as the PFS in this study reached a plateau at that timepoint.

Single-cell transcriptomics by clinical course of Mycobacterium avium complex pulmonary disease

Mycobacterium avium complex pulmonary disease (MAC-PD) has a heterogeneous clinical course. However, immune profiles associated with MAC-PD clinical course are limited. We performed single-cell RNA sequencing of peripheral blood mononuclear cells from 21 MAC-PD patients divided into three clinical courses: group A, spontaneous culture conversion; group B, stable disease without antibiotic treatment; and group C, progressive disease with antibiotic treatment. A lower proportion of NK cells and higher proportion of monocytes were noted in group C compared to combined groups A and B. The proportion of classical monocytes was higher in group C compared to groups A and B, while the proportion of non-classical monocytes decreased. EGR1, HSPA1A, HSPA1B, and CD83 were up-regulated in spontaneous culture conversion group A compared to progressive disease group C. Up-regulation of MYOM2 and LILRA4 and down-regulation of MT-ATP8, CD83, and CCL3L1 was found in progressive disease group C. PCBP1, FOS, RGCC, S100B, G0S2, AREG, and LYN were highly expressed in favorable treatment response compared to unfavorable response. Our findings may offer a comprehensive understanding of the host immune profiles that influence a particular MAC-PD clinical course and could suggest an immunological mechanism associated with the disease progression of MAC-PD.

Plasma lipidomics profiling in predicting the chemo-immunotherapy response in advanced non-small cell lung cancer.

Advanced non-small cell lung cancer (NSCLC) presents significant treatment challenges, with chemo-immunotherapy emerging as a promising approach. This study explores the potential of lipidomic biomarkers to predict responses to chemo-immunotherapy in advanced non-small cell lung cancer (NSCLC) patients. A prospective analysis was conducted on 68 NSCLC patients undergoing chemo-immunotherapy, divided into disease control (DC) and progressive disease (PD) groups based on treatment response. Pre-treatment serum samples were subjected to lipidomic profiling using liquid chromatography-mass spectrometry (LC-MS). Key predictive lipids (biomarkers) were identified through projection to latent structures discriminant analysis. A biomarker combined model and a clinical combined model were developed to enhance the prediction accuracy. The predictive performances of the clinical combined model in different histological subtypes were also performed. Six lipids were identified as the key lipids. The expression levels of PC(16:0/18:2), PC(16:0/18:1), PC(16:0/18:0), CE(20:1), and PC(14:0/18:1) were significantly up-regulated. While the expression level of TAG56:7-FA18:2 was significantly down-regulated. The biomarker combined model demonstrated a receiver operating characteristic (ROC) curve of 0.85 (95% CI: 0.75-0.95) in differentiating the PD from the DC. The clinical combined model exhibited an AUC of 0.87 (95% CI: 0.79-0.96) in differentiating the PD from the DC. The clinical combined model demonstrated good discriminability in DC and PD patients in different histological subtypes with the AUC of 0.78 (95% CI: 0.62-0.96), 0.79 (95% CI: 0.64-0.94), and 0.86 (95% CI: 0.52-1.00) in squamous cell carcinoma, large cell carcinoma, and adenocarcinoma subtype, respectively. Pathway analysis revealed the metabolisms of linoleic acid, alpha-linolenic acid, glycerolipid, arachidonic acid, glycerophospholipid, and steroid were implicated in the chemo-immunotherapy response in advanced NSCLC. Lipidomic profiling presents a highly accurate method for predicting responses to chemo-immunotherapy in patients with advanced NSCLC, offering a potential avenue for personalized treatment strategies.

Extracellular vesicle miRNAs for predicting the efficacy of late-line treatment with anlotinib in patients with lung adenocarcinoma

BackgroundAnlotinib is a targeted therapy indicated for some malignancies, including advanced non-small cell lung cancer (NSCLC). However, noninvasive biomarkers for identifying patients who will benefit from this disease remain lacking.MethodsHere, we investigated the potential of small extracellular vesicle (sEV) microRNAs (miRNAs) as predictive biomarkers for anlotinib efficacy. A total of 20 advanced NSCLC patients were enrolled. Patients were classified as having stable disease (SD) or progressive disease (PD) after the initial efficacy assessment.ResultsSeven differentially expressed miRNAs (DEMs) were identified. Among them, miR-941 was significantly upregulated in the PD group, while the others were downregulated. Furthermore, these six downregulated miRNAs (miR-30a-3p, miR-150-5p, miR-122-5p, miR-10b-5p, miR-92a-3p, and miR-150-3p) were more pronounced in nonsmoking patients.ConclusionsIt was found that sEV miRNAs have the potential to predict the benefit of anlotinib.

18F-fluorodeoxyglucose positron emission tomography-computed tomography in the localization of the lesions in the osteogenic region of breast cancer bone metastases after therapy.

Accurate efficacy evaluation of bone metastases (BMs) from breast cancer (BC) is an intractable issue in clinical practice, for which solutions are urgently needed. This study aimed to investigate the utility of 18F-fluorodeoxyglucose positron emission tomography-computed tomography (18F-FDG PET/CT) in the response evaluation of bone metastasis of BC. In total, 22 patients diagnosed with BC and BM were enrolled. These patients underwent repeated 18F-FDG PET/CT evaluations. The patients and each BM site were divided into two groups based on their response to treatment: progressive disease (PD) and nonprogressive disease (non-PD). We analyzed and compared the changes in PET and CT images, as well as the serum concentration of carcinoembryonic antigen (CEA), carbohydrate antigen 153 (CA153), alkaline phosphatase (ALP), and calcium (Ca) over the same time frame. The immunohistochemistry (IHC) of primary lesions between groups and between the primary focus and BM with high 18F-FDG uptake were compared and analyzed. Maximum standard uptake value (SUVmax) after therapy [area under the curve (AUC): 0.932] and Δ-value of SUVmax (AUC: 0.811) on 18F-FDG PET imaging proved significantly valuable for the efficacy of therapy outcomes related to BM lesions (P<0.05). In terms of overall evaluation of BM, age and human epidermal growth factor receptor 2 (HER2) expression were significantly lower in the PD group than in the non-PD group (P<0.05). There were marked differences in CEA after therapy, the changes of CEA, and CA153 (∆-value) between the groups (P<0.05). The SUVmax and Ca concentration after therapy and ∆-value of SUVmax, along with the levels of CA153, CEA, and ALP, were valuable indicators for evaluating the efficacy of individual BMs (P<0.05). IHC of BM in the PD group showed differences compared to primary lesions, with antigen Ki-67 being downregulated in metastatic lesions and HER2 being downregulated in a portion of BMs (2 of 6). Meanwhile, the expression of estrogen receptor (ER) and progesterone receptor (PR) remained relatively unchanged. 18F-FDG PET/CT confers precise assessment of the posttreatment efficacy pertaining to BM in BC. This modality facilitates the identification of poor effect lesions following extant therapies and localization for pathological assessment and may substantially contribute to evaluating therapeutic efficacy, refining treatment strategies, and predicting the disease trajectory of patients with BC and BM.

Clinical efficacy of Gamma Knife® combined with transarterial chemoembolization and immunotherapy in the treatment of primary liver cancer.

This study was designed to investigate the clinical efficacy and safety of Gamma Knife® combined with transarterial chemoembolization (TACE) and immunotherapy in the treatment of primary liver cancer. To investigate the clinical efficacy and safety of Gamma Knife® combined with TACE and immune-targeted therapy in the treatment of primary liver cancer. Clinical data from 51 patients with primary liver cancer admitted to our hospital between May 2018 and October 2022 were retrospectively collected. All patients underwent Gamma Knife® treatment combined with TACE and immunotherapy. The clinical efficacy, changes in liver function, overall survival (OS), and progression-free survival (PFS) of patients with different treatment responses were evaluated, and adverse reactions were recorded. The last follow-up for this study was conducted on October 31, 2023. Clinical evaluation of the 51 patients with primary liver cancer revealed a partial response (PR) in 27 patients, accounting for 52.94% (27/51); stable disease (SD) in 16 patients, accounting for 31.37% (16/51); and progressive disease (PD) in 8 patients, accounting for 15.69% (8/51). The objective response rate was 52.94%, and the disease control rate was 84.31%. Alanine aminotransferase, aspartate aminotransferase, lactate dehydrogenase, and alpha-fetoprotein isoform levels decreased after treatment compared with pretreatment (all P = 0.000). The median OS was 26 months [95% confidence interval (95%CI): 19.946-32.054] in the PR group and 19 months (95%CI: 14.156-23.125) in the SD + PD group, with a statistically significant difference (P = 0.015). The median PFS was 20 months (95%CI: 18.441-34.559) in the PR group and 12 months (95%CI: 8.745-13.425) in the SD + PD group, with a statistically significant difference (P = 0.002). Common adverse reactions during treatment included nausea and vomiting (39.22%), thrombocytopenia (27.45%), and leukopenia (25.49%), with no treatment-related deaths reported. Gamma Knife® combined with TACE and immune-targeted therapy is safe and effective in the treatment of primary liver cancer and has a good effect on improving the clinical benefit rate and liver function of patients.

Lymphocyte activation markers predict the therapeutic response to immune checkpoint inhibitors: A case–control study

AbstractBackgroundReports on changes in circulating immune cells induced by immune checkpoint inhibitors (ICIs) and their association with therapeutic responses are limited. This study aimed to analyze the interaction between ICIs and circulating blood cells in real‐world practice and identify biomarkers associated with therapeutic efficacy.Materials and MethodsPatients with non‐small cell lung cancer who received nivolumab, pembrolizumab, or atezolizumab monotherapy were eligible. Blood samples were collected before and 7–21, and 22–42 days after treatment, and changes in the number and characteristics of neutrophils and lymphocytes in the peripheral blood were analyzed. The efficacy of ICIs was evaluated based on the best overall response up to 3 months after treatment. The patients were divided into the following groups: patients with non‐progressive disease (non‐PD) and those with progressive disease (PD). Blood immunological factors related to treatment response were analyzed.ResultsThere were 16 and 27 patients in the non‐PD and PD groups, respectively. The non‐PD group had significantly lower pretreatment CD56+ cell (CD56+ IFN‐γ+ cell), and neutrophil counts at 7–21 days after ICI administration than the PD group. Additionally, there was a significant increase in CD8+ IFN‐γ+, and CD8+CD28+ IFN‐γ+ T‐cell counts 7–21 days after ICI administration in the non‐PD group. CD8+CD28+IFN‐γ+ T‐cell count greater than 94.6 cells/μL at 7–21 days after ICI administration was highly predictive with an AUC greater than 0.8 in the ROC curve analysis.ConclusionsPredictors of disease progression include a low activated CD56+ cell count, no increase in the neutrophil count before ICI therapy, and an increase of activated CD8+ cell count early after ICI administration. The findings will contribute to selecting patients with a favorable therapeutic response and early prediction of therapeutic response to ICI.

Clinical outcomes after adjuvant anti-PD1 therapy for high-risk resectable melanoma and predictors of response.

e21502 Background: Adjuvant anti-PD1 is the standard of care for high-risk resectable melanoma but many still suffer recurrence. We report a single institution observational study of patients who received adjuvant anti-PD1 with a particular focus on those who recurred. Methods: Through an approved protocol by Huntsman Cancer Institute IRB, patients with resected high-risk melanoma who first received anti-PD1 in the adjuvant setting were consented and followed. Clinical outcomes were assessed per RECIST 1.1, progression free survival (PFS), and overall survival (OS). Results: 186 eligible patients were included, 105 male and 81 females, median age at C1D1 58 (22-93), 12/161/7 at stage II/III/IV and 5 unstageable. Subtypes included 79 (43%) superficial spreading, 50 (27%) nodular, 16 (9%) lentigo/nevoid, 13 (7%) non-acral skin (NOS), 10 (5%) acral, 4 (2%) mucosal, and 14 (7%) others. With median follow up of 708 days (23-9599), 66 (35.5%) had progressive disease (PD), including 33 (50%) early PD and 33 (50%) late PD. Statistically significant predictors of worse outcome included age &gt; 50 (OS p = 0.043), acral subtype (PFS p = 0.023), PD-L1 IHC &lt; = 1% (OS p = 0.052, PFS p = 0.002), duration of treatment &lt; 3 months (OS p = 0.005, PFS p = 1.8E-07), early PD (OS p = 0.003, PFS p = 1.5E-6) and distant recurrence (OS p = 0.002). Trends that were not significant included: male gender (worse OS), BRAF mutation (better PFS), NF1 mutation (better PFS). No correlation between outcomes and TMB, NRAS, TERT mutation, and primary location. In the early/late PD groups, median age was 57/55 (range 28-79 / 25-84), 64/61% male, 1/0, 29/31, 3/2 stage II, III, IV. 17/13 were superficial spreading, 6/10 nodular, 2/5 acral, 2/2 lentigo, 1/0 mucosal and 4/3 other non-acral skin. Primary site was 12/12 head/neck, 9/5 trunk, 4/7 upper limb, 8/9 lower limb. BRAF was 9/11 wildtype, 15/9 mutant and 9/13 unknown. PD-L1 &gt; = 1% by IHC was 4/2. TMB mut/mb &gt; 10 was 6/5. Sites of recurrence included 6/12 local, 7/7 regional LN, 20/14 distal (3/1 in brain) relapses. For unresectable PD (13/13 early/late) response to next line systemic therapy is shown in Table 1. Conclusions: One third of patients developed PD after adjuvant anti-PD1 for high-risk melanoma. PD-L1 negativity and short duration of treatment was associated with worse outcome. Early PD corresponded to more distant metastasis, poorer OS and response to subsequent systemic therapy. Importantly most late PD can still have a favorable response by resuming anti-PD1 therapy. Further molecular study is ongoing to investigate mechanisms of resistance. [Table: see text]

A prognostic model based on selected cell state and cellular community scores in patients with advanced melanoma treated with immune checkpoint inhibitors (Ecotype-ICI score) as a predictor of ICI immunotherapeutic benefits.

9568 Background: We conducted an enhanced immune cell state atlas analysis of the data of patients with melanoma treated with ICI to investigate predictors of therapeutic benefits and mechanisms of resistance. Methods: Leveraging RNA-seq from melanoma patients (n=141) treated with ICI within the ORIEN Avatar project (NCT03977402), we constructed a prognostic model based on selected cell state and cellular community scores, also known as ecotype-ICI score ( Li. AACR 2023). We evaluated the model’s predictive value using transcriptomic data from high-risk melanoma patients treated with adjuvant ipilimumab (n=471) or interferon-α (n=248) as part of the E1609 phase 3 trial (1). RNA-seq data were initially deconvoluted for cellular community signatures using EcoTyper. The six prognostic carcinoma ecotype (CE) signatures identified (CE1, CE2, C6, CE7, CD9, CD10) were utilized for calculating a risk score based on a multivariable Cox model, which was trained using Avatar data. For additional external validation, we analyzed data from patients with metastatic melanoma treated with anti-CTLA4 ( Va. n=40), anti-PD1 ( Liu. n=121), and anti-PD1 alone or combined with anti-CTLA4 ( Gide. n=66). A series of ad hoc survival analyses, including Kaplan-Meier analysis, log-rank tests, and Cox regression were further applied. Results: The ecotype-ICI score showed strong prognostic significance in predicting overall survival (OS) in the entire group of E1609 patients (N=719; Cox P &lt; 0.0001, log-rank P &lt; 0.0001), the ipilimumab cohort (Cox P &lt; 0.000143, log-rank P =0.00011), but less so with interferon (Cox P= 0.06). CE9, characterized by its proinflammatory nature and IFN-gamma signaling, and CE10, noted for its canonical T cell state signatures, both demonstrated a leading predictive value according to multivariable Cox regression analysis. Interestingly, CE2, noted for its lymphocyte deficiency signature, also demonstrated complementary predictive value for outcomes following ipilimumab. Within the validation cohorts of public data sets noted above, the ecotype-ICI scores showed similarly strong prognostic significance in predicting OS (Gide. P = 0.045; Liu. P = 0.029; Va. P = 0.011). Ecotype-ICI also demonstrated a distinct distribution in the responder group (complete or partial response) compared to the progressive disease group, underscoring its potential as a discriminative biomarker for ICI response and survival outcomes. Conclusions: Our analysis has successfully established the utility of the immune cell state atlas in predicting therapeutic benefits with ICIs across diverse ICI treatment regimens in melanoma. We will update our results with data related to gene ontology, KEGG pathways and the most complementary pathway signatures at the meeting. 1. Tarhini, 2020.

Safety and Efficacy of CT041 in Patients With Refractory Metastatic Pancreatic Cancer: A Pooled Analysis of Two Early-Phase Trials.

CT041 is a chimeric antigen receptor (CAR)-modified T-cell therapy that specifically targets claudin18.2 in solid tumors. Here, we report the pooled analysis results of two exploratory clinical trials to evaluate CT041 in patients with previously treated pancreatic cancer (PC). These two multicenter, open-label phase I/Ib trials (CT041-CG4006, CT041-ST-01) have a similar target population and evaluation schedule. The primary objective was to assess the safety and tolerability of CT041, whereas secondary objectives included efficacy, pharmacokinetics, and immunogenicity. The combined cohort comprised 24 patients with advanced PC. Among them, five patients (20.8%) had previously received one line of therapy, whereas 19 (79.2%) received ≥2 lines of therapy. The most common treatment-emergent adverse events of grade 3 or more were preconditioning-related hematologic toxicities. Cytokine release syndrome (CRS) and GI disorders were most reported grade 1 or 2 adverse events. The overall response rate and disease control rate were 16.7% and 70.8%. The median progression-free survival (mPFS) after infusion was 3.3 months (95% CI, 1.8 to 6.2), and the median overall survival (mOS) was 10.0 months (95% CI, 5.5 to 17.6). The median duration of response (mDoR)was 9.5 months (95% CI, 2.6 to Not reached), with a DoR rate at 12 months of 50% (95% CI, 5.8 to 84.5). The mPFS (6.0 v 1.0 months, P < .001) and mOS (17.6 v 4.0 months, P < .001) were prolonged in patients achieving partial response/stable disease than the progressive disease group. CA19-9 levels had reduced by at least 30% in 17 (70.8%) patients. In patients with metastatic PC after progression on previous therapy, CT041 demonstrated a tolerable safety profile and encouraging anticancer efficacy signals. Response benefit observed here needs to be ascertained in the future.

Targeted proteomics-determined multi-biomarker profiles developed classifier for prognosis and immunotherapy responses of advanced cervical cancer.

Cervical cancer (CC) poses a global health challenge, with a particularly poor prognosis in cases of recurrence, metastasis, or advanced stages. A single biomarker is inadequate to predict CC prognosis or identify CC patients likely to benefit from immunotherapy, presumably owing to tumor complexity and heterogeneity. Using advanced Olink proteomics, we analyzed 92 oncology-related proteins in plasma from CC patients receiving immunotherapy, based upon the comparison of protein expression levels of pre-therapy with those of therapy-Cycle 6 in the partial response (PR) group and progressive disease (PD) group, respectively. 55 proteins were identified to exhibit differential expression trends across pre-therapy and post-therapy in both PR and PD groups. Enriched GO terms and KEGG pathways were associated with vital oncological and immunological processes. A logistic regression model, using 5 proteins (ITGB5, TGF-α, TLR3, WIF-1, and ERBB3) with highest AUC values, demonstrated good predictive performance for prognosis of CC patients undergoing immunotherapy and showed potential across different cancer types. The effectiveness of these proteins in prognosis prediction was further validated using TCGA-CESC datasets. A negative correlation and previously unidentified roles of WIF-1 in CC immunotherapy was also first determined. Our findings reveal multi-biomarker profiles effectively predicting CC prognosis and identifying patients benefitting most from immunotherapy, especially for those with limited treatment options and traditionally poor prognosis, paving the way for personalized immunotherapeutic treatments and improved clinical strategies.

Abstract PO3-01-12: Clinicopathologic Factors affecting response in patients with Estrogen receptor-positive and Human Epidermal Growth Factor Receptor-negative breast cancer receiving neoadjuvant chemotherapy

Abstract Background: The evolution of Neoadjuvant chemotherapy(NAC) regimen has enabled the down-staging of locally advanced breast cancer, allowing patients to undergo breast conserving surgery. NAC is known to be effective in triple-negative breast cancer (TNBC) and HER2-positive breast cancer. However, the role of NAC in hormone receptor-positive and HER2-negative (HR+HER2-) breast cancer patients remains unclear. In this study, we aimed to explore the utility of NAC for estrogen receptor-positive and HER2-negative (ER+HER2-) breast cancer patients. Methods: Clinical data were collected from 120 patients who were diagnosed with estrogen receptor (ER)-positive and HER2-negative breast cancer and received neoadjuvant chemotherapy between July, 2017 and April, 2023 at Seoul St Mary’s Hospital (Seoul, Korea). We analyzed the factors that affect clinical response subgroups, including pathologic complete response (pCR), partial response (PR), stable disease(SD), and progressive disease (PD), following neoadjuvant chemotherapy. The median follow-up period was 17 months. &amp;lt; Results: Among 120 patients after NAC, 5.8% achieved pCR, while 67.5% had a partial response. The median age at the time of surgery was 55 years at pCR group, 49 years at PR group, 47 years at SD group, and 49 years at PD group. Although the age of patients achieving pathological complete response was higher, this differences was not statistically significant. Patients achieving pCR had a higher incidence of progesterone receptor (PR) negativity (pCR 71.4% vs PR 30.9%, p=0.011) and higher levels of Ki-67 expression than those who did not achieve pCR (71.7% vs 35.6%, p=0.003). Also, there was no significant difference in Androgen receptor (AR) and HER-2 expression between the groups. Tumor size was also significantly associated with clinical response (p=0.003). However, no differences in clinical response was observed between patients with lymph node metastasis (p=0.221). Our analysis of 107 patients who were clinically N positive before NAC showed that the Ki-67 index level was the only factor found to affect nodal pCR. In addition, in the non-pCR group, patients with a Ki-67 index of less than 20% after neoadjuvant had a significantly better disease-free survival (5yr DFS, 79.8% vs 65.9%, p=0.039) Conclusion: Our analysis revealed that patients with higher levels of Ki-67 and lower level of PR expression were more likely to achieve pCR or PR. Also, decrease in Ki-67 index was confirmed to be an important prognostic factor of ER+ HER2- breast cancer. A combination of clinical and molecular factors, such as tumor size, progesterone receptor expression, and Ki-67 expression, can be used to optimize treatment plans and improve outcomes for the patient population. Citation Format: Jin Ah Lee, Young Joo Lee, Dooreh Kim, Chang Ik Yoon, Woo-Chan Park, Soo Youn Bae. Clinicopathologic Factors affecting response in patients with Estrogen receptor-positive and Human Epidermal Growth Factor Receptor-negative breast cancer receiving neoadjuvant chemotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-01-12.

Changes in Serum Interleukin-8 Levels Predict Response to Immune Checkpoint Inhibitors Immunotherapy in Unresectable Hepatocellular Carcinoma Patients.

Effective biomarkers are needed to predict the efficacy of immune checkpoint inhibitors (ICIs) therapy in hepatocellular carcinoma (HCC). We evaluated the early changes in serum interleukin-8 (IL-8) levels as a biomarker of response to ICIs in patients with unresectable HCC. Eighty patients who received ICIs therapy alone or in combination with other treatments for unresectable HCC were included. Serum was collected at baseline and 2-4 weeks after the first dose. Serum IL-8 levels were measured using by ELISA. In the progressive disease (PD) group, serum IL-8 levels increased significantly before the second dose of ICIs therapy compared with baseline levels (P < 0.001). Early changes in serum IL-8 levels were significantly associated with the response to ICIs therapy (P < 0.001). A cutoff value of 8.1% increase over the baseline most effectively predicted the response to ICIs. Increases in serum IL-8 levels > 8.1% indicated the uselessness of ICIs immunotherapy in patients with unresectable HCC. Patients with increases in serum IL-8 levels > 8.1% had significantly shorter overall survival (OS) and progression-free survival (PFS) than those with increases in serum IL-8 levels ≤ 8.1% (P < 0.001). Increases in serum IL-8 levels > 8.1% were independent prognosticators of worse OS (P = 0.003) and PFS (P < 0.001). Early changes in serum IL-8 levels, measured only 2-4 weeks after starting therapy, could predict the response to ICIs therapy, as well as OS and PFS of patients with unresectable HCC. Increases in serum IL-8 levels > 8.1% indicated the uselessness of ICIs immunotherapy and predicted worse OS and PFS.

Development and validation of a prognostic prediction model for cervical cancer patients treated with radical radiotherapy: a study based on TCGA database.

Radiotherapy or concurrent chemoradiotherapy is the standard treatment for patients with locally advanced or inoperable cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). However, treatment failure for CESC patients treated with radical radiotherapy still occurs due to local recurrence and distant metastasis. The previous prediction models were focused on all CESC patients, neglecting the prognostic differences under different treatment modalities. Therefore, there is a pressing demand to explore novel biomarkers for the prognosis and sensitivity of radiotherapy in CESC patients treated with radical radiotherapy. As a single biomarker has limited effect in stratifying these patients, our objective was to identify radioresponse-related mRNAs to ameliorate forecast of the prognosis for CESC patients treated with radical radiotherapy. Sample data on CESC patients treated with radical radiotherapy were obtained from The Cancer Genome Atlas (TCGA) database. We randomly separated these patients into a training and test cohorts using a 1:1 ratio. Differential expression analysis was carried out to identify radioresponse-related mRNA sets that were significantly dysregulated between complete response (CR) and radiographic progressive disease (RPD) groups, and univariate Cox regression analyses, least absolute shrinkage and selection operator (LASSO) method and multivariate Cox regression were performed to identify the radioresponse-related signature in the training cohort. we adopted survival analysis to measure the predictive value of the radioresponse-related signature both in the test and entire cohorts. Moreover, we developed a novel nomogram to predict the overall survival (OS) of CESC patients treated with radical radiotherapy. In addition, immune infiltration analysis and Gene Set Enrichment Analysis (GSEA) were conducted to preliminarily explore possible mechanisms. This study included a total of 92 CESC patients subjected to radical radiotherapy. We developed and verified a risk score model based on radioresponse-related mRNA. The radioresponse-related mRNA signature and International Federation of Gynecology and Obstetrics (FIGO) stage were served as independent prognostic factors for CESC patients treated with radical radiotherapy. Moreover, a nomogram integrating radioresponse-related mRNA signature with FIGO stage was established to perform better for predicting 1-, 3-, and 5-year survival rates. Mechanically, the low-risk group under the risk score of this model had a better survival status, and the distribution of CD4 T cells was potentially involved in the regulation of radiotherapy response in CESC, leading to a better survival outcome in the low-risk group. This study presents a new radioresponse-related mRNA signature that shows promising clinical efficacy in predicting the prognosis of CESC patients treated with radical radiotherapy.

Abstract 6415: Comparison the results from PD-L1 IHC and PD-L1 multiplex immunofluorescence for the prediction of anti-PD-1 immunotherapeutic response

Abstract PD-L1 immunohistochemistry (IHC) is a popular clinical test before anti PD-1/PD-L1 immunotherapy (IMT). Multiplex immunofluorescence (mIF) exhibits its advantage to evaluate more than one target on one FFPE section to provide the features of multiple target expression and co-expression signals. Here, based on our pathology controlled mIF detection system and AI based analysis data, we compared IHC PD-L1 TPS to mIF PD-L1 TPS, PD-L1 positive rate, and other target positive rates in one mIF panel, to evaluate their correlations. The correlations of IHC PD-L1 TPS, mIF PD-L1 TPS, mIF PD-L1 positive rate and other marker positive rate to anti PD-1 IMT response were further analyzed in this study. Thirty melanoma patient samples in this study have received PD-1 IMT. 13 cases exhibited partial response (PR) and 17 cases were progressive disease (PD). PFS of PR group and PD group was 27.3 and 4.8 months, respectively. Archived patient FFPE sections were examined utilizing mIF of PN 6-Plex Detection Kit (Beijing PhenoVision Bio Co., Itd) targeted CD68, CD3, CD20, S100, PD-L1 (CST, E1L3N) and PD-1. The staining images were scanned, tumor areas were labeled by pathologists and analyzed using PhenoVision mIF AI analysis system trained from Oncotopix Discovery system (Visopharm). Series sections were examined utilizing Dako PD-L1 IHC 22C3 pharmDx and TPS was scored by one clinical pathologist. mIF TPS was calculated after AI data analysis, using PD-L1/S100 co-positive cell number divided by S100 positive cell number. Data mining was performed using log-rank Mantel-Cox test, Cox regression analysis and binary logistic regression model in SPSS. In current study, the correlation between pathology scored TPS (pTPS) and mIF PD-L1 positive rate was observed (Pearson correlation coefficient (PCC)=0.447, p&amp;lt;0.05). The consistency rate between pTPS and mIF TPS was 70% with no statistical significance. Moreover, the correlation between pTPS and mIF PD1/CD3 copositive rate was detected (PCC=0.604, p&amp;lt;0.01). Interestingly, mIF PD-1/CD3 copositive rate predicted PR and PD groups (AUC=0.8, p&amp;lt;0.01). Not pTPS nor mIF PD-L1 rate showed predictions here. Current results indicate that pTPS exhibited correlation to mIF PD-L1 positive rate instead of mIF PD-L1 TPS. CD3/PD-1 copositive rate but not pTPS nor mIF PD-L1 positive rate, shows its potential to predict anti PD-1 IMT response through the pathology controlled mIF detection system and AI based analysis system. Citation Format: Hongzhe Sun, Xia Liu, Tao Jiao, Qian Guo, Haizhen Du, Shuo Han, Lin Zhu, Zhifu Zhang, Yan Kong, Na Li. Comparison the results from PD-L1 IHC and PD-L1 multiplex immunofluorescence for the prediction of anti-PD-1 immunotherapeutic response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6415.