Predictive Markers Of Response Research Articles

Predictive markers of complete pathological response to neoadjuvant chemo-immunotherapy in triple negative breast cancer.

e12650 Background: Results from the Keynote 522 clinical trial, which played a pivotal role in evaluating the efficacy of neoadjuvant pembrolizumab in combination with chemotherapy (NAICT), showed a significant improvement in pathological complete response (pCR) rates compared with chemotherapy alone. To date, no significant markers have been identified to predict pathological complete response to NAICT. The primary objective was to identify markers, both molecular and clinical, predictive of pCR to NAICT in a real-world clinical setting. Methods: The retrospective analysis included 38 consecutively treated pts with early stage TNBC who received NAICT including pembrolizumab at the Institute of Oncology, Ljubljana (OIL) between 4 January 2022 and 17 October 2023. Data collected from electronic medical records included tumour size, nodal status, UICC stage, BRCA status, systemic immune-inflammation index (SII) before NAICT and before surgery, and frequency and grade of immune-related adverse events (iAEs) (according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5). In pts who completed surgical treatment, response to treatment was assessed by pathological examination of post-treatment surgical specimens. Descriptive statistical methods were used to summarise and describe the main characteristics. Pearson chi-squared test was used to analyse categorical variables and t-test to evaluate associations between continuous variables. Results: Of the 38 pts, 28 completed surgical treatment and were further analysed. Pathohistological examination of post-treatment surgical specimens revealed pCR in 11 pts (39.3%), with residual disease in 17 pts (60.7%). Of the 17 pts without pCR, 11 pts had RCB score 2 (64.7%) and 5 pts had score 3 (29.4%). The distribution of size, nodal status, UICC stage at diagnosis, BRCA status, frequency of iAEs in correlation with pCR is shown in the Table. A borderline correlation was found between pCR and SII at the start of pembrolizumab treatment (p=0.05). Age, tumour size, nodal status, UICC stage, BRCA status, AEs, SII before surgery were not found to be predictive of pCR. Conclusions: SII at the start of pembrolizumab was found to be a borderline significant marker predictive of pCR. Other characteristics evaluated did not correlate with pCR. [Table: see text]

Ultrasound-Guided Lidocaine Injection as a Novel Predictor of Response to Botulinum for Patients With Myofascial Pain Syndrome: A Case Report.

Botulinum injection is a well-known non-surgical intervention utilized in the management of myofascial pain syndrome (MPS). However, sparse evidence exists regarding the utility of ultrasound guidance of injectate or lidocaine as a predictive marker of patient response to botulinum toxin A (BTX-A). A 39-year-old male active duty service member demonstrated typical signs and symptoms of MPS. He reported a 10-year history of neck and back spasms that were triggered by exertion but also could occur spontaneously. Based on the characteristic regional motor-sensory defects, treatment options were discussed. With shared decision-making, the patient opted to try ultrasound-guided injection of lidocaine followed by xenomin brand BotoxA. Immediately following lidocaine injection, the patient reported complete relief of symptoms. Both injections were uncomplicated, and the patient reported great reduction in symptoms during the subsequent visit 2 months later. Relief of pain following ultrasound-guided injection of lidocaine may serve as an indicator of successful patient response to BTX-A in patients with MPS.

Pharmacogenomic analysis in adrenocortical carcinoma reveals genetic features associated with mitotane sensitivity and potential therapeutics.

Adrenocortical carcinoma (ACC) is an aggressive endocrine malignancy with limited therapeutic options. Treating advanced ACC with mitotane, the cornerstone therapy, remains challenging, thus underscoring the significance to predict mitotane response prior to treatment and seek other effective therapeutic strategies. We aimed to determine the efficacy of mitotane via an in vitro assay using patient-derived ACC cells (PDCs), identify molecular biomarkers associated with mitotane response and preliminarily explore potential agents for ACC. In vitro mitotane sensitivity testing was performed in 17 PDCs and high-throughput screening against 40 compounds was conducted in 8 PDCs. Genetic features were evaluated in 9 samples using exomic and transcriptomic sequencing. PDCs exhibited variable sensitivity to mitotane treatment. The median cell viability inhibition rate was 48.4% (IQR: 39.3-59.3%) and -1.2% (IQR: -26.4-22.1%) in responders (n=8) and non-responders (n=9), respectively. Median IC50 and AUC were remarkably lower in responders (IC50: 53.4 µM vs 74.7 µM, P<0.0001; AUC: 158.0 vs 213.5, P<0.0001). Genomic analysis revealed CTNNB1 somatic alterations were only found in responders (3/5) while ZNRF3 alterations only in non-responders (3/4). Transcriptomic profiling found pathways associated with lipid metabolism were upregulated in responder tumors whilst CYP27A1 and ABCA1 expression were positively correlated to in vitro mitotane sensitivity. Furthermore, pharmacologic analysis identified that compounds including disulfiram, niclosamide and bortezomib exhibited efficacy against PDCs. ACC PDCs could be useful for testing drug response, drug repurposing and guiding personalized therapies. Our results suggested response to mitotane might be associated with the dependency on lipid metabolism. CYP27A1 and ABCA1 expression could be predictive markers for mitotane response, and disulfiram, niclosamide and bortezomib could be potential therapeutics, both warranting further investigation.

Abstract PO5-15-11: A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery

Abstract Introduction: Radiation therapy (RT) is a standard component of treatment for most patients with early-stage, hormone receptor-positive, invasive breast cancer (BC) following breast-conserving surgery (BCS). RT recommendations are primarily based on clinicopathologic (CP) factors, such as tumor size, nodal status, and histological grade. While these factors provide prognostic information, their ability to accurately identify patients at a higher risk of ipsilateral breast recurrence (IBR) or those who will significantly benefit from RT is unclear. Therefore, incorporation of additional predictive markers beyond CP factors is warranted and there remains a need to refine the selection criteria for patients who will derive the greatest benefit from RT. In this study, we aimed to explore the role of immune and metabolic signaling axes as potential predictive markers for RT response in hormone receptor-positive breast cancer patients. Methods: A cohort of 939 women from Sweden were diagnosed with BC between 1987 and 2004. A subset of 471 patients was diagnosed with T1-T2N0M0 BC and underwent BCS with negative margins. Patients were treated with BCS plus/minus RT (median dose 50Gy) based upon physician preference. Biomarkers were assayed in formalin-fixed paraffin-embedded tissue micro arrays using multiplex immunofluorescence and multi-spectral imaging in a CLIA lab (Laguna Hills, CA). Immune and metabolic axes were defined employing biomarkers and used to classify patients into three risk groups: 1) Low Risk (lower baseline risk and no RT benefit), 2) Elevated Risk (higher baseline risk and significant RT benefit), and 3) Residual Risk (higher baseline risk and suboptimal RT benefit). Risk groups were analyzed for IBR rate using Kaplan-Meier and Cox proportional hazards analyses. Risk group prognosis and RT prediction was assessed for RT-risk group interaction in multivariable analysis, adjusting for CP factors. Results: Among the patients with complete biomarker data, 261 were hormone receptor-positive, and had a median follow-up of 140 months. Median age was 62 years (28-88 years), and median tumor size was 1.1 cm (0.1-4 cm). Some patients (21%) received endocrine therapy (ET), and most (76%) received RT, with 79% of patients who received ET also receiving RT. In the overall population, RT following BCS was associated with a reduction in HR for recurrence (HR=0.3, 95%CI [0.1, 0.5], p&amp;lt; 0.001). Patients classified as Low Risk (41%) did not have a significant benefit from RT (HR=0.9, 95%CI [0.1, 8.3], p=0.95) in multivariable analysis adjusted for CP factors. For patients who were classified as Elevated Risk (31%), multivariable analysis showed a higher IBR rate without RT (HR=5.7, 95%CI [1.3, 25.1], p&amp;lt; 0.021) relative to the Low Risk group who had a significant benefit from RT (HR=0.1, 95%CI [0.02, 0.2], p&amp;lt; 0.001). Patients classified into the Residual Risk group (28%) had no significant reduction from RT (HR=0.7, 95%CI [0.2, 2.0], p=0.61). However, in multivariable analysis adjusted for CP factors, patients treated with RT in the Residual Risk group had higher IBR rates (HR=3.7, 95%CI [1.6, 8.7], p=0.0026) compared to RT-treated patients in other risk groups. The biosignature was predictive for RT benefit in multivariable analysis adjusted for CP factors (p-interaction &amp;lt; 0.001). Conclusions:The biosignature used in this study demonstrated the potential to identify patients who may derive limited benefit from RT, allowing for tailored therapeutic approaches. These findings underscore the importance of individualized treatment decisions based on risk stratification. Further clinical validation and refinement of risk stratification strategies are warranted to optimize outcomes in hormone receptor-positive, BC patients undergoing BCS. Citation Format: Troy Bremer, Karuna Mittal, Chirag Shah, Frank Vicini, Steven Shivers, Charlotta Wadsten. A Novel Biosignature to Predict Radiation Therapy Response in Early-Stage Invasive Breast Cancer Treated with Breast-Conserving Surgery [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-15-11.

Abstract PO1-18-10: ANNE: A phase II single-arm clinical trial to assess the feasibility and efficacy of neoadjuvant anastrozole in patients with luminal breast cancer and low proliferative index in TNM stages II and III

Abstract Background: Neoadjuvant endocrine therapy (NET) is recommended for the treatment of invasive breast cancer (BC), particularly luminal subtypes, in locally advanced stages. Previous randomized studies have demonstrated the benefits of aromatase inhibitors (AIs) in this context. However, in clinical practice, NET is typically reserved for elderly or frail patients who may not tolerate neoadjuvant chemotherapy. Ideally, after identifying suitable candidates for NET, patients undergo tumor re-biopsy after 2 to 4 weeks of treatment, and only those with Ki67 ≤ 10% proceed with NET. Limitations of this strategy include the standardization of re-biopsy and the reliability of Ki67 immunohistochemical analysis, as treatment decisions are based on these results. Objective: To evaluate the feasibility and efficacy of NET in postmenopausal patients with stage II and III luminal BC and to identify predictive biomarkers of therapeutic response. The efficacy will be measured by the rate of patients with Ki67 ≤ 10% after 4 weeks and Preoperative Endocrine Prognostic Index (PEPI) score 0 on the surgical specimen. The feasibility of the study will be assessed by the acceptance rate of participating in the study (recruitment rate ≥ 50%) and the inclusion rate of &amp;gt;2 patients per month. Methods: This non-randomized phase II clinical trial includes postmenopausal women with invasive breast carcinoma, Scarf-Bloom-Richardson histological grades 1 or 2, Estrogen Receptor positive (Allred ≥ 6), progesterone receptor positive (any value), HER2 negative, Ki-67 antigen &amp;lt; 50% on immunohistochemistry, stages TNM II-III, with palpable tumor ≥ 2 cm, and ECOG 0-2. All eligible patients will receive anastrozole (1 mg/day) continuously until the day before the surgical procedure or exclusion from the study (in case of disease progression during endocrine therapy). After 2 to 4 weeks, a re-biopsy of the breast tumor will be performed. If Ki67 &amp;gt; 10%, endocrine therapy will be suspended, and the patient will be excluded from the study and redirected to neoadjuvant chemotherapy (routine care) or immediate surgery (as per attending clinical oncologist and surgeon). If Ki67 ≤ 10%, the patient will continue to receive NET. Extended NET will be administered for up to 10 months, with monthly physical examinations (using calipers) and bimonthly breast ultrasound. The presence of stable disease on ultrasound at 4, 6, and 8 months indicates scheduling surgery within 2 months thereafter, and disease progression at any time indicates surgery within one month. Patients will complete the EORTC QLQ-C30 and its supplemental module BR45 questionnaires every 2 months. Toxicity will be assessed using CTCAE version 4.0, and patients will respond to 11 specific items extracted from the Brazilian version of PRO-CTCAE. The radiological response will be evaluated by RECIST 1.1. Blood samples for molecular analyses will be collected at baseline and during re-biopsy. MicroRNA profiles will be evaluated using Nanostring, and extracellular vesicles will be examined using ATR-FTIR to identify predictive markers of therapeutic response (Ki67 &amp;lt; 10%) in re-biopsy. All cases will be evaluated using PAM50 at the initial biopsy and at surgery to determine the molecular phenotype (luminal A, B, or other) and molecular response (ROR score difference). Pathologic therapeutic response will be assessed using the PEPI score in all operated cases. The sample size was calculated to be 59 patients. The study was initiated in July 2022, and since then, a total of 26 patients have been enrolled. This study is registered with The Brazilian Registry of Clinical Trials (ReBEC): RBR-5pygzhj. Citation Format: Carlos Paiva, Izabella Oliveira, Vitor Guimarães, Alinne Faria, Domício Lacerda, Anapaula Uema, Nilton Onari, Bianca Paiva, Augusto Antoniazzi, Karina Oikawa, Maria Fernanda Machado, Matheus Godinho, Cristiano Souza, Chrissie Amirati, Gustavo Teixeira, Idam de Oliveira Jr, Márcia Marques, Yara Maia. ANNE: A phase II single-arm clinical trial to assess the feasibility and efficacy of neoadjuvant anastrozole in patients with luminal breast cancer and low proliferative index in TNM stages II and III [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-18-10.

Towards Personalized Medicine in Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a chronic, incurable, multisystem, inflammatory disease characterized by synovitis and extra-articular features. Although several advanced therapies targeting inflammatory mechanisms underlying the disease are available, no advanced therapy is universally effective. Therefore, a ceiling of treatment response is currently accepted where no advanced therapy is superior to another. The current challenge for medical research is the discovery and integration of predictive markers of drug response that can be used to personalize medicine so that the patient is started on "the right drug at the right time". This review article summarizes our current understanding of predicting response to anti-rheumatic drugs in RA, obstacles impeding the development of personalized medicine approaches and future research priorities to overcome these barriers.

Immunohistochemistry of Lung Cancer Biomarkers.

Immunohistochemical (IHC) staining represents a comparatively inexpensive testing method that is attractive as a potential alternative to molecular sequencing methods or fluorescence in situ hybridization for pulmonary biomarker testing. While a variety of IHC tests directed at actionable genetic alterations have been developed and evaluated since the advent of targeted therapy, specific antibody clones for anaplastic lymphoma kinase, ROS-1, and potentially neurotrophic tropmyosin receptor kinase have been the primary antibodies that provide sufficiently robust results to be utilized as either a primary testing or screening method to direct targeted therapy. Antibodies for a variety of other targets such as epidermal growth factor receptors, for example, have lacked sufficient sensitivity and specificity to cover the range of mutations that may occur and are generally not recommended in lieu of molecular testing with the exception of limited resource settings. IHC is also used as a predictive marker for response to immunotherapy through evaluation of programmed death ligand 1 expression. In addition, multiple antibody-drug conjugates (ADCs) are under investigation, designed to deliver drugs directly to tumor cells through binding to specific target antigens. Some ADCs have already received accelerated FDA approval, and IHC was incorporated in many clinical trials evaluating ADC efficacy. As such, it is anticipated that ADCs may have a companion diagnostic IHC to guide patient selection.

Higher TIGIT+ γδ TCM cells may predict poor prognosis in younger adult patients with non-acute promyelocytic AML.

γδ T cells recognize and exert cytotoxicity against tumor cells. They are also considered potential immune cells for immunotherapy. Our previous study revealed that the altered expression of immune checkpoint T-cell immunoreceptor with immunoglobulin and ITIM domain (TIGIT) on γδ T cells may result in immunosuppression and is possibly associated with a poor overall survival in acute myeloid leukemia (AML). However, whether γδ T-cell memory subsets are predominantly involved and whether they have a relationship with clinical outcomes in patients with AML under the age of 65 remain unclear. In this study, we developed a multicolor flow cytometry-based assay to monitor the frequency and distribution of γδ T-cell subsets, including central memory γδ T cells (TCM γδ), effector memory γδ T cells (TEM γδ), and TEM expressing CD45RA (TEMRA γδ), in peripheral blood from 30 young (≤65 years old) patients with newly diagnosed non-acute promyelocytic leukemia (also known as M3) AML (AMLy-DN), 14 young patients with AML in complete remission (AMLy-CR), and 30 healthy individuals (HIs). Compared with HIs, patients with AMLy-DN exhibited a significantly higher differentiation of γδ T cells, which was characterized by decreased TCM γδ cells and increased TEMRA γδ cells. A generally higher TIGIT expression was observed in γδ T cells and relative subsets in patients with AMLy-DN, which was partially recovered in patients with AMLy-CR. Furthermore, 17 paired bone marrow from patients with AMLy-DN contained higher percentages of γδ and TIGIT+ γδ T cells and a lower percentage of TCM γδ T cells. Multivariate logistic regression analyses revealed the association of high percentage of TIGIT+ TCM γδ T cells with an increased risk of poor induction chemotherapy response. In this study, we investigated the distribution of γδ T cells and their memory subsets in patients with non-M3 AML and suggested TIGIT+ TCM γδ T cells as potential predictive markers of induction chemotherapy response.

Decreased serpin C1 in extracellular vesicles predicts response to methotrexate treatment in patients with pulmonary sarcoidosis

BackgroundSarcoidosis is a systemic granulomatous disease of unknown etiology primarily affecting the lungs. Treatment is needed when disease symptoms worsen and organ function deteriorates. In pulmonary sarcoidosis, prednisone and methotrexate (MTX) are the most common anti-inflammatory therapies. However, there is large inter-patient variability in response to treatment, and predictive response markers are currently lacking.ObjectiveIn this study, we investigated the predictive potential of biomarkers in extracellular vesicles (EVs) isolated from biobanked serum of patients with pulmonary sarcoidosis stored prior to start of therapy.MethodsProtein concentrations of a four-protein test panel of inflammatory proteins were measured in a discovery (n = 16) and replication (n = 129) cohort of patients with sarcoidosis and 47 healthy controls. Response to therapy was defined as an improvement of the absolute score of > 5% forced vital capacity (FVC) and/or > 10% diffusion lung of carbon monoxide (DLCO) after 24 weeks compared to baseline (before treatment).ResultsSerum protein levels differed between EV fractions and serum, and between sarcoidosis cases and controls. Serpin C1 concentrations in the low density lipid particle EV fraction were lower at baseline in the group of patients with a good response to MTX treatment in both the discovery cohort (p = 0.059) and in the replication cohort (p = 0.032). EV Serpin C1 showed to be a significant predictor for response to treatment with MTX (OR 0.4; p = 0.032).ConclusionThis study shows that proteins isolated from EVs harbor a distinct signal and have potential as new predictive therapy response biomarkers in sarcoidosis.

RNA M6A modification shaping cutaneous melanoma tumor microenvironment and predicting immunotherapy response.

Recent years have seen rising mortality rates linked to cutaneous melanoma (SKCM), despite advances in immunotherapy. Understanding RNA N6-methyladenosine (M6A) significance in SKCM is crucial for prognosis, tumor microenvironment (TME), immune cell presence, and immunotherapy efficacy. We analyzed 23 M6A regulators using SKCM samples from TCGA and GEO databases, identifying three M6A modification patterns linked to TME cell infiltration. Principal component analysis (PCA) yielded an M6A score for individual tumors, utilizing patient gene expression profiles and CNV data from TCGA. M6A modification patterns play a crucial role in SKCM development and progression, influencing tumor attributes such as inflammatory stage, subtype, TME interstitial activity, and genetic mutations. The M6A score independently predicts patient outcomes and correlates with improved response to immunotherapy, validated across anti-PD-1 and anti-PD-L1 therapy cohorts. M6A modifications significantly impact the TME landscape, with the M6A score serving as a predictive marker for immunotherapy response. Integrating M6A-related information into clinical practice could revolutionize SKCM management and treatment strategies.

Abstract CT289: A phase II study of Tucatinib and Ado-trastuzumab Emtansine (T-DM1) in patients with HER2-positive metastatic solid tumors and metastases to brain (TUCATEMEB)

Abstract Background: HER2 overexpression or amplification is a validated prognostic and predictive biomarker for treatments in several tumor types. The development of brain metastases is an unfortunate and common complication in patients with metastatic cancer and the incidence of brain metastases continues to grow as advances in cancer treatment extend the survival. Unfortunately many of the clinical trials still exclude patients with brain metastases. Tucatinib is a selective small molecule HER2 inibitor that has shown intracranial activity and it is approved with trastuzumab and capecitabine for treatment of patients with breast cancer including with active brain metastases. Tucatinib showed significant preclinical and clinical antitumor activity in combination with other HER2-targeted therapies, including T-DM1 in breast and other cancers. We hypothesize that the combination of tucatinib and T-DM1 will be a safe and effective treatment in HER2-positive (+) metastatic solid tumors that have metastasized to the brain. To test this hypothesis, we are conducting a Phase II Study of Tucatinib and T-DM1 in Patients with HER2+ Metastatic Solid Tumors and Metastases to Brain (TUCATEMEB). Methods: Eligible adult patients with HER2-positive solid tumors and active brain metastases (with at least one untreated brain lesion ≥0.5 cm and &amp;lt;3.0 cm) will be enrolled in the study. HER2 positivity is defined as HER2 overexpression by immunohistochemistry 3+ or 2+ and fluorescence in situ hybridization positive and/or HER2 amplification by in situ hybridization or next-generation sequencing and/or activating ERBB2 mutation. Patients will receive the study treatment in 21-day cycles: Tucatinib 300 mg orally twice daily; T-DM1 3.6 mg/kg intravenously on Day 1. The primary objective is to determine the intracranial antitumor activity of the tucatinib and T-DM1 combination per the modified RECIST in patients with HER2+ metastatic solid tumors and brain metastases. The secondary objectives are to determine the intracranial antitumor activity per the RANO-BM criteria; to evaluate the safety and tolerability, the duration of intracranial response, the overall survival, the progression free survival, the systemic antitumor activity and clinical benefit rate in patients with HER2+ metastatic solid tumors and brain metastases. Exploratory objectives are to assess predictive and pharmacodynamic markers of response and to corelate them with clinical and molecular characteristics. The efficacy endpoint will be monitored using the Bayesian optimal phase 2 BOP2 design and safety and tolerability will be monitored based on Bayesian posterior probability. Restaging brain MRI and systemic scans will be performed every 6 weeks for the first 12 weeks, and every 9 weeks thereafter. The trial opened in May 2023 and is enrolling patients (NCT05673928). Citation Format: Ecaterina E. Dumbrava, Amber M. Kennon, Rashmi K. Murthy, Emma J. Montazari, Hussein Tawbi, Jing Li, Frederick F. Lang, Gisela Sanchez, Jianbo Wang, Isabella C. Glitza, Barbara J. O'Brien, Thomas Beckham, Todd Swanson, Martin C. Tom, Uyen M. Vu, Tanisha T. Darko, Tiantian Cai, Komal Shah, Funda Meric-Bernstam, Jordi Rodon. A phase II study of Tucatinib and Ado-trastuzumab Emtansine (T-DM1) in patients with HER2-positive metastatic solid tumors and metastases to brain (TUCATEMEB) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr CT289.

Genetic Variations Affect Chemotherapy Outcomes: A Role of the Spindle-assembly Checkpoint.

Cancer patients suffer from complicated chemotoxicity. Pharmacogenomics can help stratify patients by predicting their response to treatment and susceptibility toward severe side effects. The spindle-assembly checkpoint (SAC) is an important pathway that is activated by platinum and taxane compounds and plays a crucial role in their cytotoxic activity. This study investigated a SAC component, Budding Uninhibited by Benzimidazoles 3 (BUB3), its expression, and genetic variants in advanced ovarian cancer patients treated with paclitaxel-carboplatin chemotherapy. Among 80 patients, BUB3 expression correlated with chemosensitivity, suggesting its potential as a predictive marker for chemotherapy response. However, high BUB3 expression was associated with a higher risk of poor survival. In addition, genetic polymorphisms in BUB3 (rs11248416 and rs11248419) were significantly linked to chemotherapy-related toxicities, with rs11248416 showing a negative impact on the patient's physical quality of life.

Abstract 6646: Investigating the combination of radiation and subsequent immune checkpoint inhibitor treatment in head and neck squamous cell carcinoma models

Abstract Purpose: Head and neck squamous cell carcinoma (HNSCC) is often marked by an immunosuppressive tumor microenvironment, which contributes to the dismal 10-20% response rate to immune checkpoint inhibitor (ICI) therapy in HNSCC patients. Radiotherapy (RT) is a currently standard of care and frontline therapy for HNSCC, yet resistance is common. We sought to examine the combination therapy of RT followed by ICI therapy to test if RT induces an in situ vaccination which enhances the efficacy of subsequent ICI. Methods: We utilized SCC cell lines derived from K15.KrasG12D/Smad4−/− SCCs, which mimic the progression of HPV-unrelated HNSCC, and transplanted SCC cells into immune-competent C57BL/6J mouse recipients. Mice were subjected to RT followed by anti-PD-L1/anti-TGFb therapy. CD8+ splenic T cells of responder or non-responder mice were examined by paired single-cell VDJ sequencing and single cell RNA sequencing (TCR/sc-RNAseq) to look for adaptations of the cytotoxic T cell compartment following combination therapy. Responder and non-responder tumor lines or tumors were treated with RT alone in vitro and in vivo, respectively, to examine major histocompatibility complex I (MHC-I) levels on tumor cells. Results: Responders to this combination therapy exhibited complete tumor eradication while non-responders displayed rapid tumor progression. When re-challenged with same HNSCCs cells, responders rejected implanted tumor cells while naïve recipients rapidly developed HNSCCs. Single-cell TCR sequencing of splenic CD8+ T cells revealed that responders, but not naïve recipients exhibited multiclonal CD8+ T cell expansion specifically of memory cell populations. Responder tumor cells exhibited greater levels of MHC-I protein level presentation than non-responders when stimulated with RT. Conclusions: Our data suggest that 1) elevated MHC-I by SCC tumor cells presentation driven by RT and ICI combination therapy facilitate a systemic expansion of memory CD8+ T cell clonotypes which drive anti-tumor immunity and 2) MHC-I expression at baseline or when induced by RT may serve as a predictive marker for therapeutic response to RT and ICI combination therapy in HNSCCs. Citation Format: Hanne Lind, Alexander Strait, Spencer Hall, Jack B. Goon, John D. Aleman, Samantha Chen, Philip Owens, Jing H. Wang, Christian Young, Xiao-Jing Wang. Investigating the combination of radiation and subsequent immune checkpoint inhibitor treatment in head and neck squamous cell carcinoma models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6646.

Abstract 2316: A deep Gaussian process (DGP)-based prediction model for immunecheckpoint inhibitor (ICI) response in gastric cancer (GC)

Abstract Background: Immune checkpoint inhibitors (ICIs) targeting PD-1 or PD-L1 have dramatically improved survival of patients with gastric cancer (GC). However, recent clinical trials, including KEYNOTE-059, KEYNOTE-061, and ATTRACTION-2, show that the objective response rate (ORR) for ICIs is still less than 20% in patients with advanced GC. Therefore, predicting who will respond to ICIs in advance is essential to make better treatment plans for GC patients. There are potential biomarkers to predict ICI response, but most of them can only be applied to a limited population of patients. For example, Kim ST., et al., (PMID: 30013197) show that patients with MSI-high or EBV-positive responded well to ICIs, but these subtypes account for less than 30 percent of GC patients (PMID:25079317). In this study, we propose a prediction model of ICI response using the 32 GC-specific genes that we identified from mutation data (PMID: 26635139) and showed their close association with survival and ICI response in GC (PMID: 35140202; PMID: 36508166). In addition, since the number of available GC-ICI samples is small, we design our prediction model in Bayesian and ensemble learning frameworks which are robust to small sample size problems. Methods: We collected mRNA sequencing data from GC-ICI treated patients from our institutions and publications (PMID: 30013197; PMID: 35254400; PMID: 33846173). We used 108 samples previously included in our previous work (PMID: 36508166) as the training data and 27 samples (13 responders and 14 non-responders) from (PMID: 3384617) as the test data. We built and trained a classifier to separate responders from non-responders using the expressions of the 32 genes. We proposed to use a Deep Gaussian process (GP) model, a multi-layered extension of a GP that is itself a Bayesian method. We optimized the parameters of each GP model in variational inference. To implement ensemble learning, we trained multiple DGP models with different initializations of the model parameters and data splitting (training/validation sets). For each training run, the best model was selected based on the prediction performance on the validation set, measured by AUC. The final prediction for a test sample was made by combining the prediction results of all the DGP models by taking the average. Results: We implemented the DGP-based prediction model using PyTorch in Python, and the codes will be publicly available on the GitHub repository (https://github.com/hwanglab/GC_ICI_response_prediction). We achieved a prediction performance of 0.813 AUC on the test data (sensitivity = 0.769 and specificity = 0.714). Conclusion: We propose the prediction model of ICI response, which can handle small sample size problems in the framework of Bayesian and ensemble learning. The experimental results using the GC-ICI data demonstrate that the 32 genes can be used as predictive markers for ICI response in GC. Citation Format: Sunho Park, Minji Kim, Changjin Hong, Tae Hyun Hwang. A deep Gaussian process (DGP)-based prediction model for immunecheckpoint inhibitor (ICI) response in gastric cancer (GC) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2316.

Abstract 1959: BLU-222, a potent and highly selective CDK2 inhibitor, demonstrates antitumor activity as monotherapy and as combination treatment in CCNE1-aberrant endometrial cancer models

Abstract Background: Many cyclin-dependent kinases (CDK) bind regulatory cyclins to control cell cycle progression. Aberrant CDK2 activation occurs in selected cancers (e.g., ovarian cancer, endometrial cancer) through CCNE1 amplification, leading to Rb phosphorylation, inactivation, and cell cycle checkpoint dysregulation. CCNE1 amplification and subsequent cyclin E overexpression are associated with chemotherapy resistance and shorter progression-free and overall survival. Therefore, novel therapies are needed to inhibit aberrant CDK2 activation and elicit positive clinical benefit in these patients. BLU-222 is a potent, highly selective, orally bioavailable, investigational CDK2 inhibitor with demonstrated activity in preclinical CCNE1-amplified ovarian cancer models. Here, we explored additional, specific biomarkers to predict BLU-222 sensitivity in ovarian and endometrial cancer as monotherapy or in novel combination treatment strategies. Methods: In vitro antiproliferative effect of BLU-222 was assessed by CyQuant in a panel of CCNE1-aberrant or CCNE1-normal ovarian and endometrial cell lines. Combination of BLU-222 and paclitaxel was evaluated by dosing matrix; synergy was calculated using SynergyFinder. In vivo antitumor activity of BLU-222 as a single agent or combined with paclitaxel was measured in CCNE1-aberrant endometrial cancer patient-derived xenograft (PDX) models (XenoSTART). Results: In ovarian and endometrial cell lines, CCNE1 amplification (copy number ≥ 6) predicted strong antiproliferative response to BLU-222. Using multivariate biomarker analysis, high p16 protein expression and wild-type Rb protein were identified as additional predictive markers for response to BLU-222 in CCNE1-aberrant cell lines. BLU-222 with paclitaxel was broadly active in endometrial cancer cell lines, with the strongest combination effect in cells with high CCNE1 expression, wild-type Rb protein, and low p16 protein expression. In vivo, BLU-222 elicited strong monotherapy antitumor response in CCNE1 copy number-aberrant endometrial cancer PDX models, and this effect was strengthened with the combination of paclitaxel. Conclusions: In preclinical models of CCNE1-aberrant endometrial cancer, BLU-222 demonstrated enhanced activity in combination with paclitaxel. Furthermore, Rb and p16 protein expression can be used in conjunction with CCNE1 copy number to predict response to both BLU-222 monotherapy and combination treatment. These data provide a rationale for using BLU-222 in combination with paclitaxel and demonstrate the potential benefit of using specific biomarkers to predict response. Citation Format: Nealia House, Victoria Brown, Liang Yuan, Maxine Chen, Stephanie Lee, Rentian Wu, Lakshmi Muthuswamy, Scott Ribich, Philip Ramsden, Kerrie Faia. BLU-222, a potent and highly selective CDK2 inhibitor, demonstrates antitumor activity as monotherapy and as combination treatment in CCNE1-aberrant endometrial cancer models [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1959.

Serum tumor markers for response prediction and monitoring of advanced lung cancer: A review focusing on immunotherapy and targeted therapies.

The value of serum tumor markers (STMs) in the current therapeutic landscape of lung cancer is unclear. This scoping review gathered evidence of the predictive, prognostic, and monitoring value of STMs for patients with advanced lung cancer receiving immunotherapy (IT) or targeted therapy (TT). Literature searches were conducted (cut-off: May 2022) using PubMed and Cochrane CENTRAL databases. Medical professionals advised on the search strategies. Study heterogeneity limited the evidence and inferences from the 36 publications reviewed. While increased baseline levels of serum cytokeratin 19 fragment antigen (CYFRA21-1) and carcinoembryonic antigen (CEA) may predict IT response, results for TT were less clear. For monitoring IT-treated patients, STM panels (including CYFRA21-1, CEA, and neuron-specific enolase) may surpass the power of single analyses to predict non-response. CYFRA21-1 measurement could aid in monitoring TT-treated patients, but the value of CEA in this context requires further investigation. Overall, baseline and dynamic changes in individual or combined STM levels have potential utility to predict treatment outcome and for monitoring of patients with advanced lung cancer. In advanced lung cancer, STMs provide additional relevant clinical information by predicting treatment outcome, but further standardization and validation is warranted.

Evaluation of the Prognostic Value of Pretherapeutic Magnetic Resonance Imaging in Predicting Soft Tissue Sarcoma Radiation Response: A Retrospective Study from a Large Institutional Sarcoma Imaging Database.

Background: RT-induced hyalinization/fibrosis was recently evidenced as a significant independent predictor for complete response to neoadjuvant radiotherapy (RT) and survival in patients with soft tissue sarcoma (STS). Purpose: Non-invasive predictive markers of histologic response after neoadjuvant RT of STS are expected. Materials and Methods: From May 2010 to April 2017, patients with a diagnosis of STS who underwent neoadjuvant RT for limb STS were retrieved from a single center prospective clinical imaging database. Tumor Apparent Diffusion Coefficients (ADC) and areas under the time-intensity perfusion curve (AUC) were compared with the histologic necrosis ratio, fibrosis, and cellularity in post-surgical specimens. Results: We retrieved 29 patients. The median ADC value was 134.3 × 10-3 mm2/s. ADC values positively correlated with the post-treatment tumor necrosis ratio (p = 0.013). Median ADC values were lower in patients with less than 50% necrosis and higher in those with more than 50% (120.3 × 10-3 mm2/s and 202.0 × 10-3 mm2/s, respectively (p = 0.020). ADC values higher than 161 × 10-3 mm2/s presented a 95% sensitivity and a 55% specificity for the identification of tumors with more than 50% tumor necrosis ratio. Tumor-to-muscle AUC ratios were associated with histologic fibrosis (p = 0.036). Conclusions: ADC and perfusion AUC correlated, respectively, with radiation-induced tumor necrosis and fibrosis.

Emerging potential of immunopeptidomics by mass spectrometry in cancer immunotherapy.

With significant advances in analytical technologies, research in the field of cancer immunotherapy, such as adoptive T cell therapy, cancer vaccine, and immune checkpoint blockade (ICB), is currently gaining tremendous momentum. Since the efficacy of cancer immunotherapy is recognized only by a minority of patients, more potent tumor-specific antigens (TSAs, also known as neoantigens) and predictive markers for treatment response are of great interest. In cancer immunity, immunopeptides, presented by human leukocyte antigen (HLA) class I, play a role as initiating mediators of immunogenicity. The latest advancement in the interdisciplinary multiomics approach has rapidly enlightened us about the identity of the "dark matter" of cancer and the associated immunopeptides. In this field, mass spectrometry (MS) is a viable option to select because of the naturally processed and actually presented TSA candidates in order to grasp the whole picture of the immunopeptidome. In the past few years the search space has been enlarged by the multiomics approach, the sensitivity of mass spectrometers has been improved, and deep/machine-learning-supported peptide search algorithms have taken immunopeptidomics to the next level. In this review, along with the introduction of key technical advancements in immunopeptidomics, the potential and further directions of immunopeptidomics will be reviewed from the perspective of cancer immunotherapy.

Coagulation factor V in breast cancer: a p53-regulated tumor suppressor and predictive marker for treatment response to chemotherapy

BackgroundPatients with cancer are at an increased risk of developing coagulation complications, and chemotherapy treatment increases the risk. Tumor progression is closely linked to the hemostatic system. Breast cancer tumors express coagulation factor V (FV), an essential factor in blood coagulation. The functional role of FV during treatment with chemotherapy is poorly understood and was explored in this study. ObjectivesWe aimed to investigate the role of FV in breast cancer progression by exploring associations with treatment response, gene regulation, and the functional effects of FV. MethodsThe receiver operating characteristic plotter was used to explore the predictive value of FV mRNA (F5) expression for treatment with FEC (5-fluorouracil, anthracycline, and cyclophosphamide). Breast cancer cohorts were analyzed to study treatment response to FEC. The effect of chemotherapy on F5 expression, the regulation of F5, and the functional effects of FV dependent and independent of chemotherapy were studied in breast cancer cell lines. ResultsF5 tumor expression was significantly higher in responders to FEC than in nonresponders. In vitro experiments revealed that anthracycline treatment increased the expression of F5. Inhibition and knockdown of p53 reduced the anthracycline-induced F5 expression. Mutation of a p53 half-site (c.158+1541/158+1564) in a luciferase plasmid reduced luciferase activity, suggesting that p53 plays a role in regulating F5. FV overexpression increased apoptosis and reduced proliferation slightly during anthracycline treatment. ConclusionOur study identified F5 as a p53-regulated tumor suppressor candidate and a promising marker for response to chemotherapy. FV may have functional effects that are therapeutically relevant in breast cancer.

Predictive Markers of Treatment Response to Neoadjuvant Systemic Therapy with Dual HER2-Blockade.

In patients with human epidermal growth factor receptor 2 (HER2)-positive breast cancer, achievement of pathologic complete response (pCR) is a known prognostic indicator after neoadjuvant systemic therapy (NAST). We investigated the clinicopathological factors associated with pCR in patients with HER2-positive breast cancer treated with dual HER2-blockade. In this retrospective study, 348 patients with HER2-positive breast cancer who received NAST with docetaxel and carboplatin, combined with trastuzumab and pertuzumab (TCHP), were included. Of the 348 patients with HER2 protein expression data, 278 (79.9%) had HER2 immunochemistry (IHC) 3+. Data on tumor-infiltrating lymphocyte (TIL) levels were available for 305 patients, showing a median TIL level of 20% (IQR 5-50), among which 121 (39.7%) had high TIL levels (≥30%). Estrogen receptor (ER) status (77.9% in ER-negative vs. 47.5% in ER-positive; p < 0.001), HER2 protein expression (71.6% in IHC 3+ vs. 34.3% in IHC 2+; p < 0.001), and TIL levels (71.9% in high vs. 57.6% in low; p = 0.011) were significantly associated with the pCR rate. In addition, we observed a significant link between numerical TIL levels (per 10% increment) and the pCR rate. After adjusting other clinicopathologic factors, ER status (low expression [defined as 1-9% expression] or negative), HER2 IHC 3+ and numerical TIL levels (per 10% increment), and high TIL levels (≥30%) were found to be independent predictors of pCR. Notably, in ER-negative breast cancer, the treatment response was excellent, irrespective of HER2 expression and TIL levels. Conversely, in ER-positive cases, low ER expression, HER2 IHC 3+, and numerical TIL levels or high TIL levels emerged as independent predictors of pCR. Our results suggest that ER expression, HER2 protein expression, and TIL levels serve as valuable predictors of the treatment response to neoadjuvant TCHP.