Predictive Biomarkers Of Response Research Articles

CircRNA Regulation of T Cells in Cancer: Unraveling Potential Targets.

T lymphocytes play a critical role in antitumor immunity, but their exhaustion poses a significant challenge for immune evasion by malignant cells. Circular RNAs (circRNAs), characterized by their covalently closed looped structure, have emerged as pivotal regulators within the neoplastic landscape. Recent studies have highlighted their multifaceted roles in cellular processes, including gene expression modulation and protein function regulation, which are often disrupted in cancer. In this review, we systematically explore the intricate interplay between circRNAs and T cell modulation within the tumor microenvironment. By dissecting the regulatory mechanisms through which circRNAs impact T cell exhaustion, we aim to uncover pathways crucial for immune evasion and T cell dysfunction. These insights can inform innovative immunotherapeutic strategies targeting circRNA-mediated molecular pathways. Additionally, we discuss the translational potential of circRNAs as biomarkers for therapeutic response prediction and as intervention targets. Our comprehensive analysis aims to enhance the understanding of immune evasion dynamics in the tumor microenvironment by facilitating the development of precision immunotherapy.

PD-L1 expression as a potential predictor of immune checkpoint inhibitor efficacy and survival in patients with recurrent or metastatic nasopharyngeal cancer: a systematic review and meta-analysis of prospective trials.

The predictive value of programmed death-ligand 1 (PD-L1) expression in nasopharyngeal cancer (NPC) patients receiving immune checkpoint inhibitors (ICIs) remains controversial. This study aimed to evaluate the optimal threshold of PD-L1 expression in predicting the efficacy of ICIs in patients with recurrent or metastatic (R/M) NPC. A meta-analysis was performed by retrieving relevant literature from PubMed, EMBASE, and Cochrane Library databases. Data on the pooled risk ratio (RR), mean overall survival (OS), progression-free survival (PFS), overall response rate (ORR) with 95% confidence interval, and 1%, 10%, and 25% PD-L1 expression cutoff points were obtained to examine the role of PD-L1 as a biomarker in R/M NPC patients receiving immunotherapy. In total, 1,312 patients from 14 studies were included. An improvement in PFS was observed in both patients with PD-L1 ≥ 1% (RR = 0.76, 95% CI 0.62-0.92, P = 0.005) and those with PD-L1 < 1% (RR = 0.68, 95% CI: 0.35-1.32, P = 0.26) who received first-line treatment with immunotherapy, with no significant difference between these subgroups. The pooled ORR was significantly higher in patients with PD-L1 ≥ 1% (ORR = 0.37) than in those with PD-L1 < 1% (ORR = 0.22) (P < 0.01) undergoing subsequent-line treatment. However, when we used the PD-L1 cutoff values of 10% and 25%, there was no significant difference between the positive (PD-L1 expression ≥ the cutoff value) and negative (PD-L1 expression < the cutoff value) subgroups. PD-L1 ≥ 1% also tended to be associated with better PFS and OS. Our meta-analysis suggested that first-line immunotherapy could significantly improve PFS in R/M NPC patients, regardless of the PD-L1 expression levels. Positive PD-L1 expression (≥ 1%) might be a potential predictive biomarker for a better overall response to immunotherapy in R/M NPC patients in subsequent-line setting. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42024495841 PROSPERO, identifier CRD42024495841.

Chemokine ligand 14 correlates with immune cell infiltration in the gastric cancer microenvironment in predicting unfavorable prognosis.

Gastric cancer (GC) is the world's third-leading cause of cancer-related mortality; the prognosis for GC patients remains poor in terms of a lack of reliable biomarkers for early diagnosis and immune therapy response prediction. Here, we aim to discover the connection between chemokine ligand 14 (CCL14) expression in the gastric tumor microenvironment (TME) and its clinical significance and investigate its correlation with immune cell infiltration. We assessed CCL14 mRNA expression and its interrelation with tumor-infiltrating immune cells (TILs) using bioinformatics analysis in gastric cancer. CCL14 protein expression, TILs, and immune checkpoints were detected by multiple immunohistochemistry analyses in gastric cancer tissue microarrays. Then, we conducted statistics analysis to determine the association between CCL14-related patient survival and immune cell infiltration (p < 0.05). We found that the CCL14 protein was separately expressed in the carcinoma cells and TILs in stomach cancer tissues. The CCL14 protein was related to tumor differentiation and tumor depth and positively correlated with the presentation of LAG3 and PD-L1 in gastric cancer cells. In addition, the CCL14 protein in the TILs of gastric cancer tissues was related to Lauren's type cells, T cells (CD4+ and CD8+), and CD68+ macrophages in the TME. Kaplan-Meier survival and multivariate analyses showed that the CCL14 expression in gastric cancer cells was an independent prognostic factor. Our study illustrated that CCL14 is a poor prognosis biomarker in gastric cancer, which may be associated with the potential for immunotherapy.

Evaluation of biomarkers of response in patients with breast cancer with BRCA 1/2 pathogenic variants treated with PARP inhibitors.

e15188 Background: Several prospective studies highlight the pivotal role of PARP inhibitors (PARPi) in treating BRCA-associated breast cancers (BC), demonstrating a significant overall response rate (ORR) of up to 60% in advanced BC patients with BRCA 1/2 germline pathogenic variants (PV). Despite their clinical efficacy, the factors predicting PARPi response, the mechanisms of resistance to PARPi, and the clinical strategies to overcome these challenges are still unknown. The aim of this study is to establish tissue microarrays (TMA) from primary breast tumor tissue from BC patients with BRCA1/2 PVs who were treated with PARPi and identify biomarkers of PARPi resistance. Methods: Stage 4 BC patients with BRCA 1/2 PVs who presented to the University of Texas MD Anderson Cancer Center Breast Medical Oncology clinics and were treated with PARPi between 2008-2023 were identified using our database. Available patient tissue samples were obtained from institutional tumor banks. TMA from breast tumor tissue created and evaluated by our collabrating pathologists for expression of biomarkers:Wee-1, MRE, BP1,and c-Myc. Clinical and tumor characteristics analyzed included:Age at diagnosis, treatment details, tumor characteristics including histological type, hormonal receptor status, Her-2/Neu status, grade, Ki-67 and clinical outcome. Descriptive statistics, the Fisher exact test, and the log rank test were used to report patient characteristics and outcomes. Here we report on initial TMA construct and biomarker analysis. Results: So far TMA from 12 patients treated with PARPi were succesfully constructed. Patient characteristics include: Median age of 36.5 years (29-57). Nine (75%) and 3 (25%) patients had BRCA1 and BRCA2 mutations, respectively. All patients had invasive ductal carcinoma and 9 (75%) had triple negative BC. Most patient (75%) had high nuclear grade BC and median Ki-67 was 75 (15-90). In 11 evaluable patients, the ORR was 72.7%. The median OS was 383.6 months (95% CI 62.5-383.6) and median PFS was 31.5 months (95% CI 10.8-NE). No significant difference in biomarker expression was observed between PARPi-responders and non-responders (Table1). Conclusions: This report presents unique data on novel predictive biomarkers of response and evaluates the evidence for potential biomarkers. Further analysis on a larger TMA cohort is ongoing. [Table: see text]

Validation of PD-L1 as a predictive biomarker of response in operable gastroesophageal adenocarcinoma: A meta-analysis and meta-regression of neoadjuvant chemoimmunotherapy trials.

4065 Background: Perioperative chemotherapy (ChT) is a standard for operable gastroesophageal adenocarcinoma (GEA). The addition of immune checkpoint inhibitors (ICIs) has improved pathological complete response (pCR) with unclear survival advantages in an unselected population. In the advanced setting, PD-L1 is a validated biomarker of response to ICIs. We aimed to assess its predictive role in the early stages wherein remains unexplored. Methods: We conducted a systematic review of randomised clinical trials (RCTs) of neoadjuvant or peri-operative ChT +/- ICIs in non-metastatic GEA, published between 2006-2024. Biomarker-unselected phase 2/3 or phase 3 RCTs with an active comparator were selected. Odds ratios (ORs) for pathological response (defined as pCR, ypT0, or ypT≤1), the primary outcome of this meta-analysis, were extracted and analysed using a random-effect meta-analysis. Subgroup analysis (ICI-ChT versus ChT) was performed to estimate the pooled effect of peri-operative ICIs on pathological response. Sensitivity analyses were performed to account for between-study heterogeneity. We then extracted pCR data by PD-L1 (cutoffs 1, 5, 10) from phase 2 trials of neoadjuvant ICIs+ChT or chemoradiotherapy (CRT) published between 2006-2024. Weighted Pearson trial-level correlation and a meta-regression model were used to assess the relationship of PD-L1 with pCR. Results: Nine RCTs were eligible for the analysis, one of which had two experimental arms contributing to two comparisons. Of 5359 included patients, 1302 received ICI-ChT and 4057 systemic ChT. ICI-ChT showed a significant improvement in pathological response (pooled OR 2.90, 95% CI 1.81-4.63, p&lt;0.001) with a larger effect compared to ChT-only trials (pooled OR 1.40, 95% CI 1.10-1.79, p=0.007). Results were consistent in sensitivity analyses of pCR-only, non-Asian, and since-FLOT studies. Fourteen studies were included in the phase 2 trials dataset (n=10 ICI+ChT and n=4 ICI+CRT) accounting for 708 patients receiving ICIs. PD-L1 showed a moderate positive correlation with pCR, stronger for higher cut-offs (weighted R for cut-offs 1, 5, and 10: 0.33, 0.51, and 0.65, respectively) and after exclusion of CRT trials (weighted R for cut-offs 5 and 10: 0.67 and 0.99, respectively). In a mixed-effect meta-regression model, PD-L1 ≥5 was a significant predictor of response (effect size [ES]: 0.71, 95% CI, 0.29-1.13, p=0.001), even after accounting for the backbone treatment (ChT versus CRT) (ES: 0.60, 95% CI, 0.20-1.00, p=0.003). Conclusions: Neoadjuvant ICI-ChT consistently improves pathological response in operable GEA, particularly in PD-L1-positive tumours. PD-L1 ≥5 appears a significant biomarker of pCR in non-metastatic GEA, supporting stratification by PD-L1 and biomarker-selected trials for evaluation at the individual patient level.

METTL3 as a potential predictive biomarker for immunotherapy response in metastatic head and neck cancer.

e18019 Background: Head and neck squamous cell carcinoma (HNSCC) that has metastasized presents a significant challenge for cancer treatment, requiring innovative approaches to predict immunotherapy response. Methyltransferase-like 3 (METTL3), a key component of the m6A RNA methylation machinery, has been shown to have various roles in cancer, including its potential impact on immunotherapy responses. In this study, we aim to explore the expression and related function of METTL3 in metastatic HNSCC. Methods: We investigated the expression level and its clinicopathological significance of METTL3 using The Cancer Genome Atlas Head-Neck Squamous Cell Carcinoma (TCGA-HNSC) datasets. Further validation of the METTL3 mRNA and protein expression were carried out with real-time PCR and Western blot on tissues from 112 cases of HNSCC patients. In addition, the functional role of METTL3 was investigated in vitro studies. The treatment response prediction values of METTL3 in metastatic HNSCC were calculated using ROC-plotter. Results: Our investigation revealed a significant overexpression of METTL3 in HNSCC tissue samples than in normal tissues ( p &lt; 0.001). The high expression of METTL3 was significantly correlated with nodal metastasis, advanced cancer stages, and higher tumor grades in HNSCC samples, indicating that METTL3 plays an important role in driving HNSCC progression and aggressiveness. The functional study revealed intricate connections between METTL3 and immune regulatory genes expression, highlighting its potential to influence the tumor immune microenvironment. Silencing or pharmacological inhibition of METTL3 by METTL3 inhibitor STM2457 reduced tumorigenic activity through decreasing PD-L1 expression. ROC-plotter calculations showed that the high METTL3 expression predicted powerful immunotherapy (AUC=0.588, p=6.3e-06) in metastatic HNSCC patients. Conclusions: In conclusion, METTL3 appears to be a promising predictive biomarker for the response to immunotherapy in patients with metastatic HNSCC. This research provides valuable insights into the multifaceted role of METTL3 and promising therapeutic response predictor in metastatic HNSCC.

Des-gamma-carboxy prothrombin (DCP) as a prognostic biomarker in patients with advanced hepatocellular carcinoma treated with atezolizumab/bevacizumab.

e16167 Background: Causes of variable disease response to first-line treatment with atezolizumab plus bevacizumab in patients with advanced hepatocellular carcinoma (HCC) remain unclear. Identifying tumor markers that predict treatment response and provide prognostic information may help clinicians optimize treatment strategies and patient outcomes. The role of des-gamma-carboxy prothrombin (DCP) is not well established in Hepatitis B Virus non-endemic areas. This study aimed to investigate DCP as a predictive biomarker of treatment response as well as explore prognostic implications of DCP in patients with advanced HCC. Methods: This single-center retrospective analysis evaluated DCP and radiographic response in patients with advanced HCC who received atezolizumab/bevacizumab in the first-line setting. DCP was measured at the time of best response, determined by radiographic evaluation, and compared to day one of atezolizumab/bevacizumab initiation. Elevated DCP was defined as &gt; = 7.5 ng/mL. DCP response was defined as a decrease of &gt; = 50% at response assessment compared with baseline. Comparisons of treatment effects were performed using two-tailed Fisher Exact Probability Test. Overall survival (OS) was defined as the interval between the first treatment and either the date of death or the last follow-up visit. OS was analyzed using the Kaplan–Meier method and compared between groups using the log-rank test. Results: A total of 53 patients with advanced HCC treated with atezolizumab/bevacizumab were included. Radiographic treatment responses were complete response 3.8%, partial response 22.6%, stable disease 52.8% and progression of disease 20.8%, respectively. On day one of treatment 70% of patients had an elevated DCP. Patients with DCP response had ORR of 69% (odds ratio, 15.75; 95% CI, 3.50 – 70.9; p = 0.0002) and disease control rate of 100% (p = 0.047). Conversely, patients with &gt; = 50% increase in DCP at response evaluation compared to day one of treatment had ORR of 4.5% and no response rate of 95% (p = 0.0035). Furthermore, patients who had &gt; = 50% increase in DCP had median OS of 15.4 months compared to patients without &gt; = 50% increase in DCP who had median OS of 28.4 months (HR = 2.48; 95% CI, 1.035 – 5.93; p = 0.042). There was no difference in ORR, or OS, between patients who had elevated DCP on day one of treatment and those who did not. Conclusions: DCP response correlates with objective radiographic response in patients with advanced HCC treated with atezolizumab plus bevacizumab in the first-line setting. DCP increase of &gt; = 50% correlates with decreased median OS and may serve as a negative prognostic biomarker in such patients.

Clinical and analytical validation for HRD status using targeted panel sequencing.

e17501 Background: In cancer therapy, understanding homologous recombination deficiency (HRD) is paramount, particularly due to its positive association with sensitivity to PARP inhibitor (PARPi) therapy. We propose using a targeted sequencing approach as a cost-effective and efficient alternative to the current standard of whole genome sequencing (WGS). In this study, we determine the sensitivity and clinical applications of a panel of 437 genes and over 12000 heterozygous SNP loci for evaluating HRD. Methods: HRD positivity for this assay was set at an HRD score of ≥38. To determine the limit of detection (LOD), we diluted 19 samples (4 tiers, 20 repeats each) with known HRD status. Accuracy of the assay was determined by comparing HRD status calls of 40 samples with those obtained through whole genome sequencing. Reproducibility of the assay was tested by measuring variance of HRD status for 30 samples between experimental conditions (2 operators* 3 repeats). Samples were obtained from 85 ovarian cancer (OC) patients undergoing platinum-based (Pt) chemotherapy and were profiled using our targeted sequencing assay. Results: The LOD for BRAC1/2 copy number deletions was established at a tumor purity (TP) of 30%. On the level of individual mutations, LODs range between 1.74% to 5.85% AF with a median of 2.26% AF. Repeatability analysis yields high concordance (APA= 97.83%, 95%CI= 95.34% - 99.00%; ANA= 97.73%, 95%CI= 95.13% - 98.95%), which emphasizes the precision of the assay. Comparisons against WGS based HRD scores reveal strong correlations, with Pearson coefficients of 0.975 for single sample (tumor sample only) and 0.987 for paired sample (tumor + normal sample) HRD score analysis. Through tumor profiling, we identified novel gene mutations associated with resistance to PARPi therapy in the HRD-positive population of our cohort. In the clinical setting, HRD-positive OC patients were found to experience longer progression free survival than their HRD-negative counterparts (median PFS = 18.3 vs 11.4 months, p&lt;0.05). Upon further investigation, we observed that HRD-positive patients who did not carry pathogenic alterations on BRCA1/2 gene showed significantly longer PFS than HRD-negative patients without pathogenic BRCA1/2 alterations (median PFS = 18.5 vs 11.6 months, p&lt;0.05). Conclusions: In summary, this targeted panel offers enhanced sensitivity, reliability, and precision in the assessment of HRD status for informed cancer therapy decisions. In practice, we showed that the targeted sequencing approach is a viable solution for determining HRD status of OC patients and can potentially serve as a predictive biomarker for treatment response. We believe that out assay emerges as a cornerstone in the advancement of personalized cancer care, and offers a sensitive, reliable, and precise approach to HRD assessment for improving patient outcomes.

CheckpointPx: A predictive radiology AI model of immune checkpoint inhibitor (ICI) benefit in non-small cell lung cancer (NSCLC).

8632 Background: Immune checkpoint inhibitors (ICIs) have dramatically transformed the field of non-small cell lung cancer (NSCLC) treatment. Despite the widespread use of PD-L1 as a biomarker in NSCLC, it has significant limitations as a reliable predictive biomarker for ICI response. Addressing this limitation, we have developed CheckpointPx, a non-invasive radiology AI tool to assist in ICI treatment selection for patients using only baseline CT scans. Here we demonstrate that CheckpointPx can predict improved outcomes specific to treatment with ICIs, presenting a new tool to address the shortage of reliable predictive ICI biomarkers in NSCLC and ultimately improve outcomes for patients undergoing immunotherapeutic interventions. Methods: CheckpointPx (v1.11) was trained on pre-treatment CT scans to predict response to ICIs from training data (D1: n=252 ICI recipients) from three institutions (A-C). In this study, we evaluated its performance in predicting response in two validation cohorts: a Treatment Dataset of patients receiving immunotherapy (D2: n=224, institutions B-D) and a Control Dataset of patients receiving platinum-based chemotherapy alone (D3: n=76, institution B). The response was defined as disease control per RECIST v1.1. Experienced radiologists and physicians delineated target lesions, and a deep learning model segmented pulmonary vessels. From these segmented regions, radiomic features were extracted using the Picture Health Px platform and were used to generate a radiomics benefit score and corresponding benefit groups using D1. The ability of benefit groups to stratify patients by progression-free survival (PFS) was compared across D2 and D3 to evaluate its utility in identifying patients who would benefit from ICI over chemotherapy. Results: D2 and D3 contained a mix of treatment lines (1st-4th) and predominantly late-stage tumors (Stage 3/4, &gt;85%). CheckpointPx included 16 features, such as measurements of intra-tumoral heterogeneity and vessel twistedness and branching patterns. Within the treatment dataset (D2), CheckpointPx was found to significantly stratify ICI patients by progression-free survival (PFS) with HR=0.68 (95% CI: 0.52 - 0.93, p=0.019). When applied to the control dataset, D3, benefit groups failed to stratify patients treated with chemotherapy by outcome (HR=0.91 [95% CI: 0.51-1.61], p=0.740), indicating that the signature was specific to ICI response. Conclusions: CheckpointPx demonstrated the ability to identify NSCLC patients who would benefit from ICI over chemo. The model’s association with PFS among ICI recipients, but not patients receiving chemotherapy alone, suggests that the signature is predictive of immunotherapy-related outcomes rather than generally prognostic. Additional independent, multi-site and prospective validation is warranted.

Pathologic assessment of hepatocellular carcinoma in the era of immunotherapy: a narrative review.

Immune checkpoint inhibitor (ICI)-based therapy has achieved impressive success in various cancer types. Several ICIs have been unprecedentedly approved as the treatment regimens for advanced hepatocellular carcinoma (HCC) in recent decade. Meanwhile, numerous clinical trials are being performed to exploit more ICIs into initially unresectable HCC and postoperative HCC to expectantly induce adequate tumor downstaging for further resection or implement adjuvant treatment for relapse-free survival, respectively. In this review, we aim to summarize some pragmatic histomorphologic, immunohistochemical, and molecular pathologic parameters which promisingly indicate the response of neoadjuvant/conversion ICI-related therapy and predict the efficacy of adjuvant/therapeutic ICI-related therapy for HCC. We searched PubMed using the terms hepatocellular carcinoma, immunotherapy, immune checkpoint inhibitor, immune checkpoint blockade, conversion therapy, neoadjuvant therapy, adjuvant therapy, biomarker, pathologic evaluation, pathologic assessment till February 2023. Although there is no consensus regarding the pathologic evaluation of relevant HCC specimens, it is encouraging that a few of studies have concentrated on this field, and moreover, the methods and parameters noted on other cancer types are also worthy of reference. For the pathologic assessment of HCC specimens underwent immunotherapy, a suitable sampling scheme, identifying immunotherapy-related pathologic response, and quantification of pathologic response rate should be emphasized. For the patients of HCC who are scheduled to receive immunotherapy, tumor-infiltrating lymphocyte, intratumoral tertiary lymphoid structure, programmed cell death ligand 1, Wnt/β-catenin, microsatellite instability and mismatch repair, tumor mutational burden and tumor neoantigen, as well as some other signaling pathways are the potential predictive biomarkers of treatment response of ICI. The management of HCC in the era of immunotherapy arises a brand-new pathological challenge that is to provide an immunotherapy-related diagnostic report. Albeit many related researches are preclinical or insufficient, they may tremendously alter the immunotherapy strategy of HCC in future.

Predictive biomarkers for pathological complete response in early-stage triple negative breast cancer following neoadjuvant chemotherapy.

598 Background: Identifying predictive biomarkers for early-stage triple negative breast cancer (TNBC) is essential for tailoring neoadjuvant chemotherapy (NACT) strategies effectively. Methods: We investigated potential clinical and pathological biomarkers in early-stage TNBC patients who underwent NACT regimens with anthracyclines and taxanes at a single cancer center. Medical records were scrutinized for clinical and laboratory data, with categorical variables analyzed using Fisher’s exact test. Logistic regression assessed factors associated with pathological complete response (pCR). Sensitivity and specificity of the biomarkers were explored using receiver operating characteristics (ROC) curve analyses. Results: Among 110 TNBC patients receiving anthracycline- and taxane-based NACT with complete pathology data, the median age was 48 years, 60% had stage III tumors, and 30.9% achieved pCR. Stromal tumor infiltrating lymphocytes (TILs) &gt; 10% were observed in 54.5%, 32.7% had TILs ≥30%, and 90.9% had Ki67 ≥ 50%. Univariate analysis showed no association between pCR and TILs &gt;10% (p=0.5), Ki67 ≥ 50% (p=0.4), anatomic stage (p=0.06), eosinophil-to-lymphocyte ratio (p=0.3), platelet-to-lymphocyte ratio (p=0.08), age (p=0.5), grade (p=0.6), or HER2 status (p=0.6). Neutrophil-to-lymphocyte ratio (NLR) was significantly associated with pCR in both univariate (OR 3.92; 95% CI 1.67 - 9.57; p=0.002) and multivariable analyses (Table). No association was observed between NLR ≤ 1.76 and TILs, anatomic stage, or Ki67. The optimal NLR cutoff using ROC curve was 1.76, yielding 60.6% sensitivity and 71.8% specificity for pCR. NLR cutoffs of ≤ 1.43 had specificities higher than 85%. Although TILs value was not associated with pCR in the regression model, high TILs value (≥50%) yielded a specificity of 89.4% for pCR. Conclusions: NLR emerged as a significant and independent predictor of pCR in early-stage TNBC. Prospective studies should explore this readily available biomarker in assessing neoadjuvant strategy responses. Moreover, high specificities for pCR were observed with NLR ≤ 1.43 and TILs ≥ 50%, representing cutoff values that could be explored for treatment de-escalation. [Table: see text]

Circulating tumour DNA fraction as a predictor of treatment efficacy in a randomized phase 2 trial of [177Lu]Lu-PSMA-617 (LuPSMA) versus cabazitaxel in metastatic castration-resistant prostate cancer (mCRPC) progressing after docetaxel (TheraP ANZUP 1603).

5055 Background: The TheraP trial showed that for patients with PSMA-positive, non-FDG-discordant mCRPC progressing after docetaxel, LuPSMA significantly improved biochemical and objective response rates, progression-free survival (PFS), and quality of life compared to cabazitaxel. While subsequent studies nominated high PSMA SUVmean to inform patient prioritization for LuPSMA, limited genomic data exists to guide optimal selection of these two life-prolonging therapies. We present an exploratory analysis of ctDNA fraction (ctDNA%) in baseline samples from the TheraP trial. Methods: We analyzed 180 baseline blood samples from participants who received ≥1 cycle of protocol-assigned treatment. Plasma cell-free DNA and matched white blood cell DNA underwent targeted sequencing to estimate ctDNA%. Prespecified ctDNA% categories (&lt;2%, 2-30%, and &gt;30%) were associated with previously validated imaging thresholds (PSMA SUVmean ≥10 and FDG metabolic tumor volume [MTV] ≥200mL), rate of PSA reduction ≥50% (PSA50-RR), and PFS, using chi-square test, logistic regression and Cox regression, respectively. Results: ctDNA% was evaluable in 178 (99%) participants, with ctDNA ≥2% in 85%. Median ctDNA% was 28% in ctDNA≥2% samples, and balanced across treatment arms. The odds of a PSA50 response to LuPSMA vs cabazitaxel were significantly higher for men with ctDNA &lt;2% (OR infinite, p=0.0067; PSA50-RR 100% vs 58%), with no difference at ctDNA &gt;30% (OR 1.1, p=1.0; PSA50-RR 46% vs 44%). Higher ctDNA% was associated with shorter PFS in LuPSMA- but not cabazitaxel-treated patients (LuPSMA: HR 5.0, p&lt;0.001 for ctDNA &lt;2% vs &gt;30%; cabazitaxel: HR 1.4, p=0.35 for ctDNA &lt;2% vs &gt;30%; interaction p=0.035). The predictive potential of ctDNA% was additive to PSMA SUVmean in LuPSMA-treated patients. Higher ctDNA% categories were enriched for patients with high FDG MTV and low PSMA SUVmean disease (Table). Conclusions: ctDNA% is a candidate predictive and prognostic biomarker for differential response to LuPSMA versus taxane chemotherapy in patients with molecular imaging-selected mCRPC progressing after docetaxel. Clinical trial information: NCT03392428 . [Table: see text]

Circulating tumor DNA as a predictive biomarker for pathologic response after treatment with neoadjuvant immunotherapy for localized dMMR/MSI-H colorectal cancer.

3612 Background: Neoadjuvant immunotherapy (IO) has shown promise as a potential non-surgical, curative therapy in pts with localized dMMR/MSI-H CRC. However, response assessment to IO is challenging due to difficulty measuring luminal tumors, the invasive nature of endoscopy, and known discordance between these assessment modalities. ctDNA may serve as an important, novel marker of response in this population. We evaluated pre-treatment ctDNA and ctDNA clearance and their association with pathologic complete response (pCR) in pts with localized dMMR/MSI-H CRC treated with IO. Methods: We performed a 70-gene, tumor-agnostic, NGS-based ctDNA assay (LB-70) to detect somatic mutations in a CLIA setting on 49 plasma samples collected serially from 13 pts with localized dMMR/MSI-H CRC treated with neoadjuvant pembrolizumab (mean and median cycles per pt was 8; range 1 - 16) prior to definitive surgery as part of a prospective phase 2 trial (NCT04082572). NGS was also performed on each pt’s tumor tissue to confirm mutations identified in ctDNA were tumor-specific. We defined “ctDNA clearance” as a reduction in mutational variant allele frequency (VAF) to a threshold below LB-70’s limit of detection (&lt;0.3% VAF) after neoadjuvant IO in mutations that were present in both plasma and tumor tissue. We conducted a descriptive analysis to evaluate the association between the presence of pre-treatment (“baseline”) ctDNA, ctDNA clearance, and pCR. Results: On a median number of 3 samples per pt, mutations in baseline ctDNA were detected in 7/13 pts and were confirmed orthogonally in all pts with matched tumor tissue. The mean and median VAF was 8.5% and 0.7% (range 0.3% - 26.9%). Among 10/13 pts with a pCR, none recurred clinically after median follow-up 29.7 mo. Three pts did not experience a pCR, 1 of whom had disease recurrence after surgery. pCR was observed in 6/6 pts without detectable ctDNA at baseline, while only 4/7 pts with detectable ctDNA at baseline had a pCR (100% vs 57%). Of the 7 pts with detectable ctDNA at baseline, 5 cleared their ctDNA in the neoadjuvant period, among whom, 4 had a pCR (80% likelihood of pCR with ctDNA clearance). Notably, the 1 pt who did not have a pCR despite clearing ctDNA had a near-pCR (carcinoma identified in 1/91 lymph nodes, none in cecum or colon). The mean and median number of cycles to ctDNA clearance was 2.8 and 2 (range 1 - 8). For the 2 pts who did not clear their ctDNA, neither (0%) had a pCR. Conclusions: Clearance of ctDNA following neoadjuvant IO appears to predict pCR in this pilot analysis of pts with localized dMMR/MSI-H CRC, even after a median of 2 cycles. The absence of detectable ctDNA at baseline, perhaps a surrogate for lower tumor burden at initial diagnosis, may also predict a higher likelihood for pCR. Our work suggests utility of ctDNA as a biomarker for improving risk-stratification and response assessment sensitivity.

Exploring the significance of MET overexpression by gene expression profiling versus immunohistochemistry in an EGFR-mutant lung cancer cohort.

e20600 Background: Amivantamab, an innovative EGFR-MET bispecific antibody, approved for use in EGFR exon 20 mutated lung cancers, recently demonstrated substantial clinical benefits in advanced/metastatic lung cancers with EGFR exon 19 deletion and/or L858R mutation according to data from the MARIPOSA clinical trial. Recent findings from the CHRYSALIS 2 trial indicate a potential role for MET overexpression as a predictive biomarker for response to Amivantamab combination therapy, particularly in cases resistant to Osimertinib. Methods: We retrospectively analyzed genomic profiling data in a large lung cancer cohort to characterize EGFR mutations. Additionally, we assessed MET expression via gene expression profiling (GEP) in a smaller EGFR-mutation positive sub-cohort to explore its prevalence. Results: Genomic profiling data from 799 tissue samples was included in our analysis. EGFR mutations were detected in 36%; higher prevalence of EGFR mutations was noted in our cohort (36%) vs the TCGA cohort (26%). Consistent with other studies, exon 19 deletion was the most frequent category of EGFR mutations (46%,), with EGFR p.E746_750del being the most frequent variant among them (60%). Exon 21 L858R mutation was the next most frequently detected variant (28%). Uncommon EGFR mutations were identified in 26% samples, with G719X being the most frequent among these. EGFR Exon 20 insertions contributed 6% of the EGFR variants. EGFR amplification was detected in 4.6% of samples. Of particular significance was the analysis of 21 EGFR-mutated tissue samples for targeted transcriptome analysis as a part Exacta Encyclopedic Tumor Analysis. The MET gene overexpression was detected in 52% of these samples. MET overexpression based on differential GEP identified a higher positivity rate than previously reported using MET immunohistochemistry (IHC) expression (52% vs. 36%), suggesting that GEP may be useful in identifying more patients with MET overexpression. This finding underscores the potential value of MET GEP as a biomarker, especially considering emerging data suggesting MET overexpression as a predictor for enhanced clinical benefit from the combination of Amivantamab and Lazertinib in EGFR-mutated, Osimertinib resistant patients. Furthermore, ongoing clinical trials are exploring MET overexpression as a biomarker for Amivantamab monotherapy. Conclusions: In conclusion, our study not only characterizes the landscape of EGFR mutations in a large lung cancer cohort but also highlights the prevalence of MET overexpression in EGFR-mutated samples, suggesting that MET GEP may serve as a promising predictive biomarker for enhanced clinical outcomes from Amivantamab therapy. In view of small sample size, further exploration and validation of MET overexpression by GEP is warranted in the context of EGFR-mutated advanced lung cancer.

Predictive biomarkers of response to the IRAK4/FLT3 inhibitor emavusertib in hematological malignancies.

6550 Background: Myelodysplastic neoplasms (MDS) and acute myeloid leukemia (AML) display a dynamic and diverse mutational landscape. Various mutations can induce the overexpression of a highly active long isoform of interleukin-1 receptor-associated kinase 4 (IRAK4), leading to downstream activation of transcription factors such as NFκB. This activation triggers inflammation, oncogenesis, and the survival of cancer cells. Emavusertib, a potent oral inhibitor of IRAK4 and FLT3, has demonstrated efficacy in pre-clinical leukemia models and in patients. In this abstract, we present data suggesting potential biomarkers of response to emavusertib based on clinical samples from the ongoing TakeAim Leukemia trial. Methods: In Phase I/IIa of the TakeAim Leukemia trial (NCT04278768), patients with relapsed/refractory (R/R) AML or high-risk MDS (hrMDS) received treatment with emavusertib monotherapy. Baseline and on treatment patient samples underwent RNA sequencing and proteomic analyses. RNA-seq was conducted on mononuclear cells from bone marrow or peripheral blood (n=42). Plasma proteins were quantified by the Luminex platform (n=51). Results: hrMDS patients responding to emavusertib monotherapy exhibited decreased gene expression levels of the NFκB target gene IL1β (P≤0.05) compared to non-responders. Protein analyses revealed that hrMDS responders had lower baseline levels of proliferation and migration-related factors, like Vascular Endothelial Growth Factor (VEGF-A) and CXCL12, in plasma compared to non-responders (P≤0.05). In AML samples, baseline VEGF-A levels were significantly higher in responders. The concentration of soluble PD1 (sPD1) increased in on-treatment samples in hrMDS patients (P≤0.05), but not in AML patient samples. Additionally, hrMDS samples presented lower IL2 and higher sCD47 levels compared to AML (P≤0.05). Conclusions: In this work, several baseline biomarkers indicative of a response to emavusertib were identified in patients with hematological malignancies. Responders in hrMDS showed lower baseline expression of the NFκB-associated pro-inflammatory gene, IL1β, and lower protein levels in plasma of the angiogenic factor VEGF-A and the chemokine CXCL12. In AML samples, responders have higher baseline levels of VEGF-A, indicating distinct predictive biomarkers for both pathologies. Other molecules of clinical interest, such as sPD1, showed increased concentrations in on-treatment plasma samples of hrMDS patients regardless of their response to emavusertib. Our findings highlight distinct baseline biomarkers for AML and hrMDS related to the pathophysiology of hematological malignancies. These results suggest that inflammatory and migration mediators, along with angiogenesis factors, hold potential as predictive biomarkers for assessing responses to emavusertib monotherapy treatment in hematological malignancies. Clinical trial information: NCT04278768 .

Prospective evaluation of the breast microbiome and tumor microenvironment-related biomarkers of response to neoadjuvant systemic therapy in triple negative breast cancer.

TPS615 Background: Predictive biomarkers of response to combination chemotherapy and immune-checkpoint inhibitors are urgently needed to tailor treatment recommendations for patients with early-stage triple negative breast cancer (eTNBC). Our group has demonstrated that tumour-associated microbiota in primary breast tumours represent promising and novel candidate biomarkers for patients with breast cancer. We aim to prospectively interrogate the breast cancer microbiome and tumour microenvironment (TME) of eTNBC treated with neoadjuvant chemo-immunotherapy, and correlate with clinical outcome. Methods: Trial design: This prospective translational biomarker study is enrolling patients with eTNBC suitable for standard neoadjuvant systemic therapy followed by definitive surgery. The primary objective is to evaluate the change in breast cancer microbiome composition pre- and post-therapy. Secondary objectives include correlation of the breast microbiome with pathologic complete response (pCR) and survival outcomes, tumor infiltrating lymphocytes (TILs), PDL-1 and immune subset analysis, extracellular vesicles analysis and analysis of gut microbiome. Tumor tissue samples will be collected at baseline (mandatory research biopsy) and at the time of surgery. Microbiome evaluation will be conducted using metagenomic sequencing to assess changes in the relative abundance of microbial taxa. Blood and stool samples will be collected and analysed at baseline, on-treatment, at the time of surgery and post-operatively for secondary endpoints. Statistical analysis: Hierarchical clustering of samples based on relative abundance of the operational taxonomic units (OTUs) with sample composition at family and genus level will be performed. Alpha Diversity (Shannon Diversity Index) and Beta Diversity (Jaccard Similarity Index) will be analysed. Principal component analysis (PCA) and Random Forest analysis will be performed for classification and clustering analysis. Comparison of taxa or functions between clinical cohorts will be performed (two tailed Z test) and corrected using the false discovery rate to determine Q-values. Thirty patients will be recruited over 18-24 months. Current status: This University College Cork sponsored trial received ethics approval from the CREC in January 2024 and recruitment is ongoing. Those interested can contact uccctg@ucc.ie. This trial will provide a deeper insight into the potential role of the local breast microbiome as a predictive biomarker for response to neoadjuvant therapy in patients with eTNBC. The results will guide further studies exploring optimal immunomodulatory combinations for the treatment of TNBC and may provide evidence regarding future therapeutic targeting of the breast cancer microbiome.

Concordance of PD-L1 combined positive score (CPS) analysis between primary gastric cancer and matched peritoneal metastasis.

e16068 Background: Peritoneum represents one of the most common metastatic sites of gastroesophageal adenocarcinoma (GEA) and is associated with poor prognosis. Programmed death-ligand 1 (PD-L1) expression is a recognized predictive biomarker of response to immune checkpoint inhibitors (ICIs) in the first-line setting. However, data from pivotal trials showed poorer clinical efficacy of ICIs in the sub-set of patients with peritoneal involvement, regardless of PD-L1 score magnitude. Here, we investigated the temporal and spatial heterogeneity of PD-L1 expression between primary tumor and matched peritoneal metastasis. Methods: PD-L1 expression according to CPS was determined by immunohistochemistry using VENTANA PD-L1 (SP263) assays on formalin-fixed paraffin-embedded (FFPE) tumor tissues derived from 22 patients treated at our institution for advanced GEA from September 2015 to August 2023. Concordance rate of PD-L1 expression between primary tumor and matched peritoneal metastasis using PD-L1 CPS cut-off of 1 and 5 was reported (spatial heterogeneity); additionally, concordance between PD-L1 value before and after the administration of systemic treatments was analyzed (temporal heterogeneity). Results: 12(54.5%)/5(22.7%) primary tumor samples and 12(54.5%)/1(4.5%) peritoneal metastases showed PD-L1 CPS ≥ 1/ ≥ 5, respectively. Concordance of PD-L1 CPS between primary and peritoneal specimens was 54.5% and 72.7% according to CPS cuts-off of 1 and 5, respectively, highlighting marked spatial heterogeneity. High concordance rate (94%) was reported between negative PD-L1 CPS primary tumor samples and matched peritoneal metastases, against the cut-off of CPS ≥ 5; in contrast, none of the positive primary tumor samples retained PD-L1 expression in the peritoneum. Evident temporal heterogeneity of PD-L1 expression was also observed, with 56% concordance against CPS ≥ 5 in the pre- versus post-treatment comparison. Conclusions: PD-L1 expression in GEA is characterized by spatial and temporal heterogeneity which is more prominent for lower CPS cut-offs values. This evidence could hamper its role as predictive biomarker for ICIs. The high intra-patient discordance rate of PD-L1 CPS expression between positive primary tumor samples and matched peritoneal metastases suggests that peritoneal specimens should not be recommended as the preferred source for PD-L1 assessment.

Pretreatment neutrophil to lymphocyte ratio as a predictor of pathological complete response to neoadjuvant immunotherapy in early breast cancer.

e12545 Background: Neoadjuvant immunotherapy has been increasingly used in early breast cancer, while lack of accessible predictive biomarkers of response remains an open question. High pretreatment neutrophil to lymphocyte ratio (NLR) was associated with worse prognosis and treatment responses to neoadjuvant chemotherapy in multiple cancers including breast cancer. However, it remains unclear whether NLR was associated with response to neoadjuvant immunotherapy in early breast cancer. Methods: We retrospectively analyzed 89 early breast cancer patients who received neoadjuvant chemotherapy in combination with at least 4 cycles of immunotherapy and subsequent breast surgery in Sun Yat-sen University Cancer Center. Pretreatment NLR was calculated, and Miller-Payne grade 5 in primary tumor site was considered pathological complete response (pCR) to neoadjuvant therapy. Univariate and multivariate analyses were used to evaluate the associations between clinicopathological markers and pCR. Results: 49.4% (44/89) of the patients achieved pCR. Compared to non-pCR patients, pCR patients had significantly lower pretreatment NLR (1.93 vs 2.87, p&lt;0.001) and lower percentage of pretreatment cT3/T4 stage (11.4% vs 37.7%, p=0.006), and received more cycles of neoadjuvant immunotherapy (6.5 vs 6.0, p&lt;0.05). More pCR patients received TCb based neoadjuvant therapy (86.4% vs 51.1%, p&lt;0.001). In multivariate analysis, the pretreatment NLR (p=0.002) and cT3/T4 (p=0.010, as compared to cT1/T2) were independent predictive factors for pCR. Conclusions: Lower pretreatment NLR was associated with higher possibility of achieving pCR in early breast cancer treated with neoadjuvant immunotherapy. [Table: see text]

LC3AB protein-based gene (PbG) signatures as an indicator of relapse even after achieving pathological complete response.

e12552 Background: The application of tissue-based quantitative protein and morphological profiling of breast cancer tissues combined with RNA sequencing provides a flexible and generally applicable and scalable method to develop Protein-based Gene (PbG) signatures with significant prognostic value. Methods: A racially and subtype diverse breast cancer cohort (N=555) with available subset of RNA-seq data was used to develop gene expression-based signatures by stratifying patients according to protein expression (IHC) based on survival information and tumor lymphocyte infiltration (TILs) using survival-derived cutoff values. The predictive value of these signatures was then compared with other popular biomarkers scoring systems such as ROR.score, and OncotypeDx (Gene 21). Here we describe the predictive value of these signatures is evaluated by logistic regression modeling of publicly available gene expression data (N=996) from patients receiving neoadjuvant chemotherapy (anthracycline +/- taxane) with a final validation in an independent cohort (N=443) receiving similar therapy. Results: A model of PbG-derived signature from Kaiso, LC3A/B IHC and quantitative TIL-measurements together with ROR score, MAPK, PTEN, Immune and Gene21 signatures show significant prediction of distant metastasis-free survival in all patients: (DMFS, AUC= 0.737, 95% CI: 0.665- 0.819); and in non-pCR patients DMSF (AUC= 0.71, 95% CI: 0.633-0.773). When examining the role of all those markers among the patients who achieved the pCR and had relapse, the LC3A/B PbG-derived score was found to be highly predictive of those patients who would not achieve pCR and ultimately have recurrent disease. Conclusions: PbG-based signatures utilizing on LC3A/B protein values offer a novel and clinically relevant predictive biomarker of response to therapy and relapse in breast cancer patients.

Prediction of pathological response to neo-adjuvant chemotherapy using texture parameters of initial 18-FDG PET/CT in estrogen receptor positive/Her2 negative (ER+/HER2-) early breast cancer (eBC).

e12567 Background: ER+/HER2- phenotype represents 70% of eBC and is itself a heterogenic entity in which neoadjuvant chemotherapy (NAC) can be indicated. Early change in 18F-FDG uptake on PET/CT, using standardized uptake value (SUV) parameter, has been shown as a predictive biomarker of response to NAC. However, this parameter can be defaulted in ER+/HER2- BC. The objective of this work was to evaluate the correlation of textural parameters of initial 18-FDG PET/CT with histologic response in ER+/HER2- eBC. Methods: All patients receiving NAC for ER+/HER2- eBC, with 18F-FDG PET/CT prior NAC at the Integrated Center for Oncology Pays de Loire were included between 2012 and 2023. Twenty-nine metabolic and volumetric parameters and 42 textural features (DOSISOFT software, Planet Onco v2.0) were collected. Pathological response was assessed for each breast tumoral lesion in case of multifocal disease. Results: A total of 161 patients with 179 lesions were included. Medium age was 51 years old. 89% and 10% of patients presented a cT1 or cT2 tumoral lesion, 78% with lymph node involvement, 44% with a grade 3 and 46% with a HER2 low status. 21% of patients achieved a pathological complete response in breast (ypT0) and 11% a complete histologic response (ypT0N0). Examinations were performed using three types of PET/CT systems (GE Healthcare and Philips Healthcare). In order to harmonize radiomics data Combat method was used. Thirteen semi-quantitative (MTV and SUVmax, SUVmean, SUVmean(EVPc), SUVpeak, TLG for weight-normalized and lean-body-mass-normalized, respectively) and 6 textural parameters (entropy, homogeneity, SRE, LRE, LGZE, and HGZE) were retained. For all radiomics features used in this study, no statistical difference was found between ypT0 and non-ypT0 patients (p ≥ 0.05). Conclusions: Selected textural parameters were not associated with histologic response in our cohort of ER+/HER2- eBC. However, many other textural features, not retained in this study because influenced by acquisition parameters and segmentation methods, could be taken into account. An ongoing preliminary work (as resampling, normalization) is needed to improve their robustness before evaluating their interest in predicting histologic response to NAC.