Predictive Biomarkers Of Response Research Articles

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rates that have not changed over the past decades, in the face of advancements in treatments and biomarkers, which have improved survival for other cancers. Delays in diagnosis are frequent, leading to more disfiguring treatments and poor outcomes in patients. The clinical challenge lies in identifying those patients at highest risk for developing OSCC. Oral epithelial dysplasia (OED) is a precursor of OSCC with highly variable behavior across patients. There is no reliable clinical, pathologic, histologic or molecular biomarker to determine individual risk in OED patients. Similarly, there are no robust biomarkers to predict treatment outcomes or mortality of OSCC patients. This review aims to highlight advancements in artificial intelligence (AI)-based methods to develop predictive biomarkers of OED transformation to OSCC or predictive biomarkers of OSCC mortality and treatment response. Machine-learning based biomarkers, such as S100A7, demonstrate promising appraisal for the risk of malignant transformation of OED. Machine learning-enhanced multiplex immunohistochemistry (mIHC) workflows examine immune cell patterns and organization within the tumor immune microenvironment to generate outcome predictions in immunotherapy. Deep learning (DL) is an AI-based method using an extended neural network or related architecture with multiple "hidden" layers of simulated neurons to combine simple visual features into complex patterns. DL-based digital pathology is currently being developed to assess OED and OSCC outcomes. The integration of machine learning in epigenomics aims to examine the epigenetic modification of diseases and improve our ability to detect, classify, and predict outcomes associated with epigenetic marks. Collectively, these tools showcase promising advancements in discovery and technology, which may provide a potential solution to addressing the current limitations in predicting OED transformation and OSCC behavior, both of which are clinical challenges that must be addressed in order to improve OSCC survival.

Updates on the natural history and clinical characteristics of NSAID-ERD

Nonsteroidal Anti-Inflammatory Drug Exacerbated Respiratory Disease (NSAID-ERD) is a distinct clinical syndrome characterized by NSAID hypersensitivity, asthma, and nasal polyposis. Its diagnosis is challenging due to variable presentations and a lack of simple tests, leading to diagnostic delays. Recent research has revealed its genetic predispositions, environmental triggers, and associations with atopy and second-hand tobacco smoke exposure or smoking cessation. Despite its severity, diagnostic awareness remains low, leading to the delay in effective management. Therapeutically, NSAID-ERD necessitates multidisciplinary approaches, often combining surgical interventions with medical management, including aspirin desensitization and biologic agents. However, predictive biomarkers for treatment response remain elusive. Understanding the underlying mechanisms driving NSAID-ERD pathogenesis and identifying reliable biomarkers are crucial for enhancing diagnostic accuracy and refining targeted therapeutic strategies for this debilitating condition. This review aims to provide a thorough understanding of NSAID-ERD, covering its history, clinical features, epidemiology, diagnosis, systemic and molecular biomarkers, available treatment options, and avenues for future research.

Nasal Epithelium Transcriptomics Predict Clinical Response to Elexacaftor/Tezacaftor/Ivacaftor.

Elexacaftor/tezacaftor/ivacaftor (ETI) has made a substantial positive impact for people living with CF (pwCF). However, there can be substantial variability in efficacy, and we lack adequate biomarkers to predict individual response. We thus aimed to identify transcriptomic profiles in nasal respiratory epithelium that predict clinical response to ETI treatment. We obtained nasal epithelial samples from pwCF prior to ETI initiation and performed a transcriptome-wide analysis of baseline gene expression to predict changes in FEV1 (∆FEV1), year's best FEV1 (∆ybFEV1), and body mass index (∆BMI). Using the top differentially expressed genes (DEGs), we generated transcriptomic risk scores (TRS) and evaluated their predictive performance. The study included 40 pwCF aged ≥6 years (mean 27.7 [SD=15.1] years; 40% female). After ETI initiation, FEV1 improved ≥5% in 22 (61.1%) participants and ybFEV1 improved ≥5% in 19 (50%). TRS were constructed using top over-expressed and under-expressed genes for each. Adding the ∆FEV1 TRS for to a model with age, sex, and baseline FEV1 increased the AUC from 0.41 to 0.88; the ∆ybFEV1 TRS increased the AUC from 0.51 to 0.88; and the ∆BMI TRS increased the AUC from 0.46 to 0.92. Average accuracy was thus ~85% in predicting the response to the three outcomes. Results were similar in models further adjusted for F508del zygosity and previous CFTR modulator use. In conclusion, we identified nasal epithelial transcriptomic profiles that help accurately predict changes in FEV1 and BMI with ETI treatment. These novel TRS could serve as predictive biomarkers for clinical response to modulator treatment in pwCF.

Blood Tumor Mutational Burden Alone Is Not a Good Predictive Biomarker for Response to Immune Checkpoint Inhibitors in Patients With Gastrointestinal Tumors.

There has been a controversy about the predictive value of tissue-TMB-H for immune checkpoint inhibitors (ICIs) with limited data regarding blood-TMB (bTMB) in GI tumors. We aim to evaluate the predictive value of bTMB compared with MSI-H in GI tumors. Patients with unresectable/metastatic GI cancer, harboring either MSS with bTMB-H (≥10mut/Mb) or dMMR/MSI-H who received ICI were included. We compared ICIs' efficacy between MSS-bTMB-H (N=45) versus MSI-H (N=50) in GI tumors. Ninety-five patients were identified with the majority having colorectal (49.5%) or esophagogastric (34.7%) cancers. MSS-bTMB-H group had more esophagogastric cancer and later-line ICI recipients, with no significant differences in other known prognostic variables. At a median follow-up of 9.4 months, MSI-H group showed superior ORR (58.0% vs. 26.7%), DCR (84.0% vs. 42.2%), DoR (not-reached vs. 7.6mo), PFS (22.5 vs. 3.8mo), and OS (Not-reached vs. 10.1mo) compared with MSS-bTMB-H. Multivariable analysis showed that MSI-H was an independent favorable factor over MSS-bTMB-H for PFS (HR=0.31, CI 0.15-0.63, P=0.001) and OS (HR=0.33, CI 0.14-0.80, P=0.014). MSI-H group showed favorable outcomes compared with MSS-bTMB-16+ (ORR: 58.0% vs. 26.9%; DCR: 84.0% vs. 42.3%; PFS:22.5 vs. 4.0mo) and MSS-bTMB-20+ (ORR: 58.0% vs. 31.6%; DCR: 84.0% vs. 42.1%; PFS:22.5 vs. 3.2mo). There was no difference between MSS-bTMB10-15 compared with MSS-bTMB-16+ in ORR, DCR, and PFS, or between MSS-bTMB10-19 compared with MSS-bTMB20+. Regardless of bTMB cutoff at 10, 16, or 20, bTMB-H did not appear to be a predictive biomarker in MSS GI tumors in this retrospective analysis.

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.

Changes of circulating tumor cells expressing CD90 and EpCAM in early-phase of atezolizumab and bevacizumab for hepatocellular carcinoma

Circulating tumor cells (CTCs) are noninvasive biomarkers that can indicate the therapeutic response and prognosis. The study aimed to investigate the cellular characteristics of CTCs focusing on monitoring during atezolizumab and bevacizumab (Atezo-Bev) therapy in patients with hepatocellular carcinoma (HCC). Peripheral blood samples were collected from 10 healthy controls and 40 patients with HCC. CTCs enriched using RosetteSep™ Human CD45 depletion cocktail were analyzed by multiparametric flow cytometry. CTC isolation was based on PanCK(+)CD45(−) cells, and CTCs exhibiting markers CD90, CD133, EpCAM, or vimentin. The total number of CTCs and the number of CTCs expressing CD90, CD133, EpCAM, and vimentin were correlated with the BCLC stage of HCC. The change in total CTC count accurately reflected the initial response to Atezo-Bev therapy. The numbers and mean fluorescence intensity of the CTC subsets expressing CD90 and EpCAM molecules decreased in patients with partial response/stable disease, and increased in patients with progressive disease and were markedly correlated with overall survival. CD90(+) and EpCAM(+) CTCs may be candidate biomarkers for the early prediction of the treatment response and the overall survival of patients with HCC receiving Atezo-Bev therapy.

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

Recently, low human epidermal growth factor receptor 2 (HER2) protein expression has been proposed as a predictive biomarker for response to the 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 with levels seen in breast cancer that 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. Although 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 a detectable target (ie, 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.

Serial Changes of Circulating Tumor Cells in Patients with Hepatocellular Carcinoma Treated with Atezolizumab Plus Bevacizumab.

Immune checkpoint inhibitors have promising outcomes in patients with hepatocellular carcinoma (HCC); however, there is no reliable biomarker for predicting disease progression. Circulating tumor cells (CTCs) derived from peripheral blood have attracted attention in monitoring therapeutic efficacy. In this study, CTCs were serially collected from HCC patients undergoing atezolizumab plus bevacizumab (Atezo+Bev), and changes in molecular expression and CTC numbers were analyzed to identify effective biomarkers. Changes in CTC numbers during Atezo+Bev reflected the tumor volume. Targeted RNA sequencing with next-generation sequencing (NGS) revealed that patients with elevated transforming growth factor (TGF)-β signaling molecules had a poorer response, whereas those with elevated apoptosis signaling molecules had a favorable response. In addition, compared with changes in CTC counts, changes in TGF-β signaling molecule expression in CTCs accurately and promptly predicted treatment response. Overall, NGS analysis of CTC-derived RNA showed that changes in TGF-β signaling molecules predict treatment response earlier than changes in CTC counts. These findings suggest that changes in the expression of TGF-β molecules in CTCs could serve as novel biomarkers for the early prediction of therapeutic response in patients with unresectable HCC undergoing Atezo+Bev.

Biomarker screen for efficacy of oncolytic virotherapy in patient-derived pancreatic cancer cultures

Pancreatic ductal adenocarcinoma (PDAC) is a tumour entity with unmet medical need. To assess the therapeutic potential of oncolytic virotherapy (OVT) against PDAC, different oncolytic viruses (OVs) are currently investigated in clinical trials. However, systematic comparisons of these different OVs in terms of efficacy against PDAC and biomarkers predicting therapeutic response are lacking. We screened fourteen patient-derived PDAC cultures which reflect the intra- and intertumoural heterogeneity of PDAC for their sensitivity to five clinically relevant OVs, namely serotype 5 adenovirus Ad5-hTERT, herpes virus T-VEC, measles vaccine strain MV-NIS, reovirus jin-3, and protoparvovirus H-1PV. Live cell analysis, quantification of viral genome/gene expression, cell viability as well as cytotoxicity assays and titration of viral progeny were conducted. Transcriptome profiling was employed to identify potential predictive biomarkers for response to OV treatment. Patient-derived PDAC cultures showed individual response patterns to OV treatment. Twelve of fourteen cultures were responsive to at least one OV, with no single OV proving superior or inferior across all cultures. Known host factors for distinct viruses were retrieved as potential biomarkers. Compared to the classical molecular subtype, the quasi-mesenchymal or basal-like subtype of PDAC was found to be more sensitive to H-1PV, jin-3, and T-VEC. Generally, expression of viral entry receptors did not correlate with sensitivity to OV treatment, with one exception: Expression of Galectin-1 (LGALS1), a factor involved in H-1PV entry, positively correlated with H-1PV induced cell killing. Rather, cellular pathways controlling immunological, metabolic and proliferative signaling appeared to determine outcome. For instance, high baseline expression of interferon-stimulated genes (ISGs) correlated with relative resistance to oncolytic measles virus, whereas low cyclic GMP-AMP synthase (cGAS) expression was associated with exceptional response. Combination treatment of MV-NIS with a cGAS inhibitor improved tumour cell killing in several PDAC cultures and cells overexpressing cGAS were found to be less sensitive to MV oncolysis. Considering the heterogeneity of PDAC and the complexity of biological therapies such as OVs, no single biomarker can explain the spectrum of response patterns. For selection of a particular OV, PDAC molecular subtype, ISG expression as well as activation of distinct signaling and metabolic pathways should be considered. Combination therapies can overcome resistance in specific constellations. Overall, oncolytic virotherapy is a viable treatment option for PDAC, which warrants further development. This study highlights the need for personalised treatment in OVT. By providing all primary data, this study provides a rich source and guidance for ongoing developments. German National Science Foundation (Deutsche Forschungsgemeinschaft, DFG), German Cancer Aid (Deutsche Krebshilfe), German National Academic Scholarship Foundation (Studienstiftung des deutschen Volkes), Survival with Pancreatic Cancer Foundation.

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.