Predictive Biomarkers Of Response Research Articles

SIRT1 promotes chemoradiotherapy resistance in esophageal squamous cell carcinoma.

Introduction Identifying accurate biomarkers for predicting response to chemoradiotherapy (CRT) in patients with esophageal squamous cell carcinoma (ESCC) is a critical challenge. The protein SIRT1, recognized for its implications in longevity, has been associated with tumor promotion in ESCC. However, data regarding its correlation with CRT sensitivity remains unreported. Therefore, in this study, we aimed to investigate the relationship between SIRT1 expression and CRT sensitivity and concurrently assess the effect of SIRT1 knockdown on CRT sensitivity in ESCC. Methods This study included 73 patients who underwent radical esophagectomy after CRT. SIRT1 expression in pre-treatment endoscopic biopsies was assessed through immunostaining, followed by a comparative analysis of CRT effects on surgical specimens. Small interfering RNA was used to attenuate SIRT1 expression in TE5 and TE10 cells, which were then subjected to cisplatin treatment at varying doses and concentrations and irradiation with X-rays, respectively. Results High SIRT1 tissue expression was significantly associated with CRT resistance. Multivariate analysis identified high SIRT1 expression as an independent biomarker for poor CRT response. In TE-5 and TE-10 cells, SIRT1 knockdown significantly decreased cell viability and increased sensitivity to cisplatin and radiation treatment compared to that of the negative control. Conclusion Our study results demonstrate the potential of SIRT1 as a predictive biomarker for CRT response in ESCC, highlighting the heightened sensitivity to CRT upon the transcriptional inactivation of SIRT1. Targeting SIRT1 emerges as a promising strategy for enhancing the efficacy of CRT for ESCC.

Pan-cancer analysis of disulfidptosis with potential implications in prognosis, immune microenvironment, and drug resistance in human cancer.

To get a systematic assessment of disulfidptosis-related genes across human cancers and explore the predictive role of disulfidptosis in cancer drug sensitivity. We developed a score-level model to quantify the level of disulfidptosis in 33 human cancers using TCGA data. The mRNA expression and protein levels of disulfidptosis-related genes in human cancer cells and tissues were detected and retrieved from the Human Protein Atlas. Multiomics bioinformatic analyses were performed to evaluate disulfidptosis-related gene characteristics as well as the effect of disulfidptosis on the cancer immune microenvironment and drug resistance. Thirty cancers showed significantly different expression levels of disulfidptosis-related genes between normal and tumor samples. The mRNA expression and protein level of disulfidptosis-related genes were consistent with TCGA databases in lung cancer and hepatocellular carcinoma. We also found that altered levels of the disulfidptosis score expression were usually related to patient prognosis, and high expression of disulfidptosis-related genes was associated with drug resistance in different cancer types. Our study illustrates the characterization of disulfidptosis in multiple cancer types and highlights its potential value as a predictive biomarker of drug response, which can pave the way for further investigation of the prognostic and therapeutic potential of disulfidptosis.

Quantitative Measurement of HER2 Expression in Non-Small Cell Lung Cancer with a High Sensitivity Assay

Recently, low HER2 protein expression has been proposed as a predictive biomarker for response to antibody-drug conjugate trastuzumab deruxtecan (T-DXd) in metastatic breast cancer. HER2 expression in non-small cell lung cancer (NSCLC) patients has never been carefully measured, and little is known about the frequency of cases with unamplified but detectable levels of the protein. Although some HER2-targeted therapies have been studied in NSCLC patients, they have been restricted to those with genomic ERBB2 gene alterations, which only represent relatively rare cases of NSCLC. Still, emerging investigations of T-DXd in NSCLC have shown promise in patients with unamplified HER2. Taken together, we hypothesize that there may be many cases of NSCLC with levels of HER2 protein expression comparable to levels seen in breast cancer who benefit from T-DXd. Here, we used a previously validated, analytic, quantitative immunofluorescence (QIF) assay that is more sensitive than legacy clinical HER2 immunohistochemistry assays. We measured HER2 protein levels in NSCLC cases to determine the proportion of cases with detectable HER2 expression. Using cell line calibration microarrays alongside our QIF method enabled us to convert HER2 signal into units of attomoles per mm2. We found that over 63% of the 741 analyzed NSCLC cases exhibited HER2 expression above the limit of detection, with more than 17% of them exceeding the lower limit of quantification. While the threshold for response to T-DXd in breast cancer is still unknown, many cases of NSCLC have expression in a range comparable to breast cancer cases with immunohistochemistry scores of 1+ or 2+. Our assay could potentially select NSCLC cases with detectable target (i.e., HER2) that might benefit from HER2 antibody-drug conjugates, irrespective of ERBB2 genomic alterations.

Genomic and Epigenomic Biomarkers of Immune Checkpoint Immunotherapy Response in Melanoma: Current and Future Perspectives

Immune checkpoint inhibitors (ICIs) demonstrate durable responses, long-term survival benefits, and improved outcomes in cancer patients compared to chemotherapy. However, the majority of cancer patients do not respond to ICIs, and a high proportion of those patients who do respond to ICI therapy develop innate or acquired resistance to ICIs, limiting their clinical utility. The most studied predictive tissue biomarkers for ICI response are PD-L1 immunohistochemical expression, DNA mismatch repair deficiency, and tumour mutation burden, although these are weak predictors of ICI response. The identification of better predictive biomarkers remains an important goal to improve the identification of patients who would benefit from ICIs. Here, we review established and emerging biomarkers of ICI response, focusing on epigenomic and genomic alterations in cancer patients, which have the potential to help guide single-agent ICI immunotherapy or ICI immunotherapy in combination with other ICI immunotherapies or agents. We briefly review the current status of ICI response biomarkers, including investigational biomarkers, and we present insights into several emerging and promising epigenomic biomarker candidates, including current knowledge gaps in the context of ICI immunotherapy response in melanoma patients.

BRCA1 foci test as a predictive biomarker of olaparib response in ovarian cancer patient-derived xenograft models

Standard therapy for high-grade ovarian carcinoma includes surgery followed by platinum-based chemotherapy and poly-ADP ribose polymerase inhibitors (PARPis). Deficiency in homologous recombination repair (HRD) characterizes almost half of high-grade ovarian carcinomas and is due to genetic and epigenetic alterations in genes involved in HR repair, mainly BRCA1/BRCA2, and predicts response to PARPi. The academic and commercial tests set up to define the HRD status of the tumor rely on DNA sequencing analysis, while functional tests such as the RAD51 foci assay are currently under study, but have not been validated yet and are available for patients. In a well-characterized ovarian carcinoma patient-derived xenograft platform whose response to cisplatin and olaparib, a PARPi, is known, we assessed the association between the BRCA1 foci score, determined in formalin-fixed paraffin-embedded tumor slices with an immunofluorescence technique, and other HRD biomarkers and explored the potential of the BRCA1 foci test to predict tumors’ response to cisplatin and olaparib. The BRCA1 foci score was associated with both tumors’ HRD status and RAD51 foci score. A low BRCA1 foci score predicted response to olaparib and cisplatin, while a high score was associated with resistance to therapy. As we recently published that a low RAD51 foci score predicted olaparib sensitivity in our xenobank, we combined the two scores and showed that the predictive value was better than with the single tests. This study reports for the first time the capacity of the BRCA1 foci test to identify HRD ovarian carcinomas and possibly predict response to olaparib.

In-house homologous recombination deficiency testing in ovarian cancer: a multi-institutional Italian pilot study

AimsPoly (ADP-ribose) polymerase (PARP) inhibitors (PARPIs) represent a standard of care for the clinical management of high-grade serous ovarian cancer (HGSOC). The recognition of homologous recombination deficiency (HRD) has emerged...

Electroencephalogram synchronization measure as a predictive biomarker of Vagus nerve stimulation response in refractory epilepsy: A retrospective study.

There are currently no established biomarkers for predicting the therapeutic effectiveness of Vagus Nerve Stimulation (VNS). Given that neural desynchronization is a pivotal mechanism underlying VNS action, EEG synchronization measures could potentially serve as predictive biomarkers of VNS response. Notably, an increased brain synchronization in delta band has been observed during sleep-potentially due to an activation of thalamocortical circuitry, and interictal epileptiform discharges are more frequently observed during sleep. Therefore, investigation of EEG synchronization metrics during sleep could provide a valuable insight into the excitatory-inhibitory balance in a pro-epileptogenic state, that could be pathological in patients exhibiting a poor response to VNS. A 19-channel-standard EEG system was used to collect data from 38 individuals with Drug-Resistant Epilepsy (DRE) who were candidates for VNS implantation. An EEG synchronization metric-the Weighted Phase Lag Index (wPLI)-was extracted before VNS implantation and compared between sleep and wakefulness, and between responders (R) and non-responders (NR). In the delta band, a higher wPLI was found during wakefulness compared to sleep in NR only. However, in this band, no synchronization difference in any state was found between R and NR. During sleep and within the alpha band, a negative correlation was found between wPLI and the percentage of seizure reduction after VNS implantation. Overall, our results suggest that patients exhibiting a poor VNS efficacy may present a more pathological thalamocortical circuitry before VNS implantation. EEG synchronization measures could provide interesting insights into the prerequisites for responding to VNS, in order to avoid unnecessary implantations in patients showing a poor therapeutic efficacy.

Abstract IA009: Single strand DNA GAP accumulation as a functional biomarker for DNA Repair Inhibitors

Abstract Deficiency of homologous recombination (HR)-mediated DNA repair occurs through genetic or epigenetic inactivation of the BRCA1 and BRCA2 (BRCA1/2) genes. HR-deficiency also provides unique opportunities for targeted therapy, through the mechanism of synthetic lethality, as exemplified by the hypersensitivity of BRCA1/2-mutated tumors to PARP inhibitors (PARPi). To date, several PARP inhibitors have been approved for clinical use. The promising clinical response of patients with germline BRCA1/2-mutations prompted the use of PARPi for patients with somatic BRCA1/2 mutations as well. In addition, these results extended the use of PARPi for various types of ovarian, breast, pancreatic, and prostate tumors with HR defects. PARPi resistance is emerging as the major obstacle to clinical effectiveness in patients with HR-deficient tumors. PARPi resistance results from several independent mechanisms, leading to the restoration of Homologous Recombination and/or Replication Fork stabilization. The absence of alternative options for patients with tumors with innate or acquired resistance underlines the urgency to develop additional therapeutics. More recent studies have identified new synthetic lethal opportunities for BRCA1/2 deficient tumors. Knockout of the genes for POLQ (DNA polymerase theta) or for USP1 (Ubiquitin Specific Protease 1) results in killing of these tumors, and inhibitors of these enzymes are emerging as promising agents for HR-deficient tumors. POLQ and USP1 expression is particularly high in subtypes of breast and ovarian tumors with defects in HR. As a result, POLQi or USP1i in HR-deficient tumors induces cell death. POLQi or USP1i can synergize with PARPi in killing HR-deficient tumors or PARPi-resistant tumors. BRCA1/2 deficient tumors have an increase in single strand DNA gaps (ssGAPs) near replication forks. Treatment with PARPi results in an increase in the size and number for these ssGAPs, ultimately leading to DSBs and cell death. Interestingly, PARPi resistance results, at least in part, from the ability of resistant cells to close the ssGAPs through enhanced POLQ and USP1 activity, thereby providing a rationale for the combination of PARP1, POLQi, and USP1 in HR-deficient cancers. USP1 inhibition was synergistic with PARP and POLQ inhibition in BRCA1-mutant cells, with enhanced ssDNA gap accumulation. Moreover, this synergy was observed in a set of patient-derived ovarian cancer organoids (PDOs), thus confirming the sensitivity of BRCA1-deficient cells to inhibition by these agents. The accumulation of ssDNA gaps after treatment with a USP1i, PARP, or POLQi correlated with the sensitivity to these drugs in all models tested. Ovarian cancer PDOs provide a powerful tool for detecting drug synergy and for rapid in vitro sensitivity testing. The detection of ssDNA gap accumulation may be a useful predictive biomarker for response to DNA Repair inhibitors as monotherapy or in combination in ongoing clinical trials. Citation Format: Alan D. D'Andrea. Single strand DNA GAP accumulation as a functional biomarker for DNA Repair Inhibitors [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr IA009.

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]

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 > = 7.5 ng/mL. DCP response was defined as a decrease of > = 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 > = 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 > = 50% increase in DCP had median OS of 15.4 months compared to patients without > = 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 > = 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<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<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.

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) > 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 >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]

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.

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.

Prospective observational study of nutritional and immunological indices as predictive biomarkers of response to immune checkpoint inhibitors in non-small cell lung cancer (ICI-PREDICT study).

e20524 Background: Nutritional and immunological indices, including controlling nutritional status (CONUT) score, skeletal muscle area (SMA), and neutrophil-to-lymphocyte ratio (NLR) have been reported as predictors of response to immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC). The aim of this prospective, multicenter study is to evaluate the clinical impact of pre- or early post-treatment changes in nutritional and immunological indices on treatment outcomes in patients with advanced NSCLC treated with first-line ICIs. Methods: We enrolled 301 advanced NSCLC patients treated with ICIs (monotherapy or combined with chemotherapy) as first-line therapy, without any oncogene mutations, and available data on programmed cell death-ligand 1 (PD-L1) expression (150 in training and 151 in validation cohorts) from March 2020 to November 2022. The CONUT score, SMA at the L3 level (cm2/m2), and NLR, were evaluated before treatment initiation and at the first response evaluation. Cut-off values were determined by receiver operating characteristic curves with objective response as the outcome in the training cohort. The primary endpoint was progression-free survival (PFS). For exploratory study, serum before treatment was collected to measure 15 muscle-derived cytokines (Apelin, BDNF, CX3CL1, EPO, FABP3, FSTL1, FGF21, IL-6, IL-15, Irisin, LIF, Musclin, Myostatin, OSM, and SPARC) (n = 123). Results: The median follow-up period and PFS was 17.5 (range: 7.3-39.4) and 6.9 (range: 0.1-31.5) months, respectively. In the training cohort, men (hazard ratio [HR]: 0.52, 95% confidence interval [CI]: 0.30-0.90, p = 0.0183), ΔCONUT < 0 (HR: 0.59, 95% CI: 0.35-0.98, p = 0.0431), and ΔSMA > −0.13 (HR: 0.56, 95% CI: 0.33-0.96, p = 0.0333) were independent predictors for PFS. In the validation cohort, PD-L1 ≥ 50% (HR: 0.54, 95% CI: 0.34-0.84, p = 0.0061), NLR < 3.65 (HR: 0.47, 95% CI: 0.30-0.74, p = 0.0011), and ΔSMA > −0.13 (HR: 0.61, 95% CI: 0.38-0.98, p = 0.0421) were independent predictors for PFS. In the exploratory study, multivariate analysis including muscle-derived cytokines (continuous variables) revealed that performance status = 0 (HR: 0.24, 95% CI: 0.12-0.48, p < 0.0001), without baseline prednisone (≥ 10 mg/day) (HR: 0.17, 95% CI: 0.05-0.58, p = 0.0213), smoking history (HR: 0.34, 95% CI: 0.14-0.81, p = 0.0269), and FSTL1 (HR: 0.97, 95% CI: 0.93-0.99, p = 0.0185) were independent predictors of PFS. Conclusions: ΔSMA was the only factor validated as an independent predictor of PFS. The underlying biological mechanisms may be related to skeletal muscle-derived FSTL1. Clinical trial information: UMIN000040450.

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<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<0.05). More pCR patients received TCb based neoadjuvant therapy (86.4% vs 51.1%, p<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.

Correlation of TILs indices generated by visual review and digital computational algorithm with outcomes from preoperative chemotherapy for TNBC in TBCRC 030.

555 Background: Predictive biomarkers for response to neoadjuvant chemotherapy (NAC) in early-stage triple negative breast cancer (TNBC) are needed. Stromal tumor infiltrating lymphocytes (TILs) are prognostic and predictive in TNBC, typically scored by visual examination (VE) of H&E stained slides. Evaluation of image-based surrogate signatures for TILs and other immune profiles by computational assessment (CA) of slides may offer greater precision and more comprehensive assessment of the immune microenvironment. This study was designed to evaluate TILs by VE and CA methods and investigate through blinded assessment the predictive capacity of immune activation. Methods: The phase II study TBCRC 030 randomized patients (pts) with BRCA1/2-proficient stage I-III TNBC to cisplatin (C) or paclitaxel (T) NAC, with primary endpoint response at surgery. TILs were visually scored on a continuous scale by a single experienced pathologist on digitized H&E images of pre-treatment core needle biopsies (CNB). CA used the 4D QPOR platform’s statistical physics and tumor biology based algorithm to quantify cell cycle aberrations and microenvironment dynamics including TILs, immune response (IHI), and combined immune response and cell cycle signature (CmbI) as continuous biomarkers from digitized CNB images. Evaluation of TILs by VE and CA were each correlated with response (RCB 0/1) or non-response (RCB 2/3) to NAC. Receiver operator characteristic (ROC) curves with area under the curve (AUC) measures and odds ratios (OR) with 95% confidence intervals were used to assess the predictive performance of each biomarker. Results: Of 139 evaluable pts, 121 had usable data for TILs by both VE and CA (59 received C, 62 received T). Descriptive statistics for biomarkers by response are shown in the Table. Notably TILs score by VE was significantly predictive of response, as was CA CmbI. TILs by VE had OR 1.86 (95% CI 1.24, 2.87, p=0.031) and AUC 0.69 (95% CI 0.57, 0.66), whereas CA CmbI had OR 1.54 (95% CI 1.00, 2.42, p=0.053) and AUC 0.62 (95% CI 0.51, 0.73). CA TILs and IHI were not predictive of response. TILs by VE predicted response to T (OR 2.91 95% CI 1.56, 6.16, p=0.002) but not C (OR 1.22 95% CI 0.67, 2.18 p=0.49). Conclusions: In this analysis of TBCRC 030, VE of baseline TILs and CA CmbI were predictive of response to NAC for TNBC, however CA did not outperform VE. TILs predicted response to specific chemotherapy. Automated computational evaluation of TILs or the broader immune microenvironment is an emerging field which may allow accurate and reproducible assessment of these important biomarkers. Clinical trial information: NCT01982448 . [Table: see text]