Glycosylation in cancer as a source of biomarkers.

INTRODUCTION: Glycosylation, the process of glycan synthesis and attachment to target molecules, is a crucial and common post-translational modification (PTM) in mammalian cells. It affects the protein's hydrophilicity, charge, solubility, structure, localization, function, and protection from proteolysis. Aberrant glycosylation in proteins can reveal new detection and therapeutic Glyco-biomarkers, which help to improve accurate early diagnosis and personalized treatment. This review underscores the pivotal role of glycans and glycoproteins as a source of biomarkers in human diseases, particularly cancer. AREAS COVERED: This review delves into the implications of glycosylation, shedding light on its intricate roles in cancer-related cellular processes influencing biomarkers. It is underpinned by a thorough examination of literature up to June 2024 in PubMed, Scopus, and Google Scholar; concentrating on the terms: (Glycosylation[Title/Abstract]) OR (Glycan[Title/Abstract]) OR (glycoproteomics[Title/Abstract]) OR (Proteoglycans[Title/Abstract]) OR (Glycomarkers[Title/Abstract]) AND (Cancer[Title/Abstract]) AND ((Diagno*[Title/Abstract]) OR (Progno*[Title/Abstract])). EXPERT OPINION: Glyco-biomarkers enhance early cancer detection, allow early intervention, and improve patient prognoses. However, the abundance and complex dynamic glycan structure may make their scientific and clinical application difficult. This exploration of glycosylation signatures in cancer biomarkers can provide a detailed view of cancer etiology and instill hope in the potential of glycosylation to revolutionize cancer research.

Designing Rigorous and Efficient Clinical Utility Studies for Early Detection Biomarkers.

Before implementing a biomarker in routine clinical care, it must demonstrate clinical utility by leading to clinical actions that positively affect patient-relevant outcomes. Randomly controlled early detection utility trials, especially those targeting mortality endpoint, are challenging due to their high costs and prolonged duration. Special design considerations are required to determine the clinical utility of early detection assays. This commentary reports on discussions among the National Cancer Institute's Early Detection Research Network investigators, outlining the recommended process for carrying out single-organ biomarker-driven clinical utility studies. We present the early detection utility studies in the context of phased biomarker development. We describe aspects of the studies related to the features of biomarker tests, the clinical context of endpoints, the performance criteria for later phase evaluation, and study size. We discuss novel adaptive design approaches for improving the efficiency and practicality of clinical utility trials. We recommend using multiple strategies, including adopting real-world evidence, emulated trials, and mathematical modeling to circumvent the challenges in conducting early detection utility trials.

Atlas of Metastatic Gastric Cancer Links Ferroptosis to Disease Progression and Immunotherapy Response.

BACKGROUND & AIMS: Metastases from gastric adenocarcinoma (GAC) lead to high morbidity and mortality. Developing innovative and effective therapies requires a comprehensive understanding of the tumor and immune biology of advanced GAC. Yet, collecting matched specimens from advanced, treatment-naïve patients with GAC poses a significant challenge, limiting the scope of current research, which has focused predominantly on localized tumors. This gap hinders deeper insight into the metastatic dynamics of GAC. METHODS: We performed in-depth single-cell transcriptome and immune profiling on 68 paired, treatment-naïve, primary metastatic tumors to delineate alterations in cancer cells and their tumor microenvironment during metastatic progression. To validate our observations, we conducted comprehensive functional studies both in vitro and in vivo, using cell lines and multiple patient-derived xenograft and novel mouse models of GAC. RESULTS: Liver and peritoneal metastases exhibited distinct properties in cancer cells and dynamics of tumor microenvironment phenotypes, supporting the notion that cancer cells and their local tumor microenvironments co-evolve at metastatic sites. Our study also revealed differential activation of cancer meta-programs across metastases. We observed evasion of cancer cell ferroptosis via GPX4 up-regulation during GAC progression. Conditional depletion of Gpx4 or pharmacologic inhibition of ferroptosis resistance significantly attenuated tumor growth and metastatic progression. In addition, ferroptosis-resensitizing treatments augmented the efficacy of chimeric antigen receptor T-cell therapy. CONCLUSIONS: This study represents the largest single-cell dataset of metastatic GACs to date. High-resolution mapping of the molecular and cellular dynamics of GAC metastasis has revealed a rationale for targeting ferroptosis defense in combination with chimeric antigen receptor T-cell therapy as a novel therapeutic strategy with potential immense clinical implications.

Circulating microRNA Panel for Prediction of Recurrence and Survival in Early-Stage Lung Adenocarcinoma.

Early-stage lung adenocarcinoma (LUAD) patients remain at substantial risk for recurrence and disease-related death, highlighting the unmet need of biomarkers for the assessment and identification of those in an early stage who would likely benefit from adjuvant chemotherapy. To identify circulating miRNAs useful for predicting recurrence in early-stage LUAD, we performed miRNA microarray analysis with pools of pretreatment plasma samples from patients with stage I LUAD who developed recurrence or remained recurrence-free during the follow-up period. Subsequent validation in 85 patients with stage I LUAD resulted in the development of a circulating miRNA panel comprising miR-23a-3p, miR-320c, and miR-125b-5p and yielding an area under the curve (AUC) of 0.776 in predicting recurrence. Furthermore, the three-miRNA panel yielded an AUC of 0.804, with a sensitivity of 45.8% at 95% specificity in the independent test set of 57 stage I and II LUAD patients. The miRNA panel score was a significant and independent factor for predicting disease-free survival (p < 0.001, hazard ratio [HR] = 1.64, 95% confidence interval [CI] = 1.51-4.22) and overall survival (p = 0.001, HR = 1.51, 95% CI = 1.17-1.94). This circulating miRNA panel is a useful noninvasive tool to stratify early-stage LUAD patients and determine an appropriate treatment plan with maximal efficacy.

Baseline Serum Inflammatory Proteins Predict Poor CAR T Outcomes in Diffuse Large B-cell Lymphoma.

A subset of patients with diffuse large B-cell lymphoma (DLBCL) treated with CD19 chimeric antigen receptor (CAR) T-cell therapy have poor clinical outcomes. We report serum proteins associated with severe immune-mediated toxicities and inferior clinical responses in 146 patients with DLBCL treated with axicabtagene ciloleucel. We develop a simple stratification based on pre-lymphodepletion C reactive protein (CRP) and ferritin to classify patients into low-, intermediate-, and high-risk groups. We observe that patients in the high-risk category were more likely to develop grade ≥3 toxicities and had inferior overall and progression-free survival. We sought to validate our findings with two independent international cohorts demonstrating that patients classified as low-risk have excellent efficacy and safety outcomes. Based on routine and readily available laboratory tests that can be obtained prior to lymphodepleting chemotherapy, this simple risk stratification can inform patient selection for CAR T-cell therapy. SIGNIFICANCE: CAR T-cell therapy has changed the treatment paradigm for patients with relapsed/refractory hematologic malignancies. Despite encouraging efficacy, a subset of patients have poor clinical outcomes. We show that a simple clinically applicable model using pre-lymphodepletion CRP and ferritin can identify patients at high risk of poor outcomes. This article is featured in Selected Articles from This Issue, p. 80.

Protein biomarkers and alternatively methylated cell-free DNA detect early stage pancreatic cancer.

OBJECTIVE: Pancreatic ductal adenocarcinoma (PDAC) is commonly diagnosed at an advanced stage. Liquid biopsy approaches may facilitate detection of early stage PDAC when curative treatments can be employed. DESIGN: To assess circulating marker discrimination in training, testing and validation patient cohorts (total n=426 patients), plasma markers were measured among PDAC cases and patients with chronic pancreatitis, colorectal cancer (CRC), and healthy controls. Using CA19-9 as an anchor marker, measurements were made of two protein markers (TIMP1, LRG1) and cell-free DNA (cfDNA) pancreas-specific methylation at 9 loci encompassing 61 CpG sites. RESULTS: Comparative methylome analysis identified nine loci that were differentially methylated in exocrine pancreas DNA. In the training set (n=124 patients), cfDNA methylation markers distinguished PDAC from healthy and CRC controls. In the testing set of 86 early stage PDAC and 86 matched healthy controls, CA19-9 had an area under the receiver operating characteristic curve (AUC) of 0.88 (95% CI 0.83 to 0.94), which was increased by adding TIMP1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.06), LRG1 (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02) or exocrine pancreas-specific cfDNA methylation markers at nine loci (AUC 0.92; 95% CI 0.88 to 0.96; p=0.02). In the validation set of 40 early stage PDAC and 40 matched healthy controls, a combined panel including CA19-9, TIMP1 and a 9-loci cfDNA methylation panel had greater discrimination (AUC 0.86, 95% CI 0.77 to 0.95) than CA19-9 alone (AUC 0.82; 95% CI 0.72 to 0.92). CONCLUSION: A combined panel of circulating markers including proteins and methylated cfDNA increased discrimination compared with CA19-9 alone for early stage PDAC.

Modulating a prebiotic food source influences inflammation and immune-regulating gut microbes and metabolites: insights from the BE GONE trial.

BACKGROUND: Accessible prebiotic foods hold strong potential to jointly target gut health and metabolic health in high-risk patients. The BE GONE trial targeted the gut microbiota of obese surveillance patients with a history of colorectal neoplasia through a straightforward bean intervention. METHODS: This low-risk, non-invasive dietary intervention trial was conducted at MD Anderson Cancer Center (Houston, TX, USA). Following a 4-week equilibration, patients were randomized to continue their usual diet without beans (control) or to add a daily cup of study beans to their usual diet (intervention) with immediate crossover at 8-weeks. Stool and fasting blood were collected every 4 weeks to assess the primary outcome of intra and inter-individual changes in the gut microbiome and in circulating markers and metabolites within 8 weeks. This study was registered on ClinicalTrials.gov as NCT02843425, recruitment is complete and long-term follow-up continues. FINDINGS: Of the 55 patients randomized by intervention sequence, 87% completed the 16-week trial, demonstrating an increase on-intervention in diversity [n = 48; linear mixed effect and 95% CI for inverse Simpson index: 0.16 (0.02, 0.30); p = 0.02] and shifts in multiple bacteria indicative of prebiotic efficacy, including increased Faecalibacterium, Eubacterium and Bifidobacterium (all p < 0.05). The circulating metabolome showed parallel shifts in nutrient and microbiome-derived metabolites, including increased pipecolic acid and decreased indole (all p < 0.002) that regressed upon returning to the usual diet. No significant changes were observed in circulating lipoproteins within 8 weeks; however, proteomic biomarkers of intestinal and systemic inflammatory response, fibroblast-growth factor-19 increased, and interleukin-10 receptor-α decreased (p = 0.01). INTERPRETATION: These findings underscore the prebiotic and potential therapeutic role of beans to enhance the gut microbiome and to regulate host markers associated with metabolic obesity and colorectal cancer, while further emphasizing the need for consistent and sustainable dietary adjustments in high-risk patients. FUNDING: This study was funded by the American Cancer Society.

Tumor-Associated and Systemic Autoimmunity in Pre-Clinical Breast Cancer among Post-Menopausal Women.

Autoantibodies to tumor-associated antigens (anti-TAA) are potential biomarkers for breast cancer, but their relationship systemic autoimmunity as ascertained though antinuclear antibodies (ANA) is unknown and warrants consideration given the common occurrence of autoimmunity and autoimmune diseases among women. The relationship between anti-TAAs and ANA among women who were later diagnosed with breast cancer and others who remained cancer free in the Women's Health Initiative cohort. The study sample included 145 post-menopausal women with baseline ANA data. A total of 37 ANA-positive women who developed breast cancer (i.e., cases; mean time to diagnosis 6.8 years [SE 3.9]) were matched to a random sample of 36 ANA-negative cases by age and time to diagnosis. An age-matched control sample was selected including 35 ANA-positive and 37 ANA-negative women who did not develop breast cancer (i.e., controls; follow-up time ~13 years [SE 3]). Baseline sera were assessed for Immunoglobulin G (IgG) antibodies, measured by custom microarray for 171 breast and other cancer-associated TAA. We used linear regression to estimate cross-sectional associations of ANA with log-transformed anti-TAA among cases and controls. Most anti-TAA did not vary by ANA status. Two anti-TAA were elevated in ANA-positive compared to ANA-negative cases: anti-PGM3 (p = 0.004) and anti-TTN (p = 0.005, especially in cases up to 7 years before diagnosis, p = 0.002). Anti-TAA antibodies were not generally related to ANA, a common marker of systemic autoimmunity. Associations of ANA with particular antigens inducing autoimmunity prior to breast cancer warrant further investigation.

Evolution of immune and stromal cell states and ecotypes during gastric adenocarcinoma progression.

Understanding tumor microenvironment (TME) reprogramming in gastric adenocarcinoma (GAC) progression may uncover novel therapeutic targets. Here, we performed single-cell profiling of precancerous lesions, localized and metastatic GACs, identifying alterations in TME cell states and compositions as GAC progresses. Abundant IgA+ plasma cells exist in the premalignant microenvironment, whereas immunosuppressive myeloid and stromal subsets dominate late-stage GACs. We identified six TME ecotypes (EC1-6). EC1 is exclusive to blood, while EC4, EC5, and EC2 are highly enriched in uninvolved tissues, premalignant lesions, and metastases, respectively. EC3 and EC6, two distinct ecotypes in primary GACs, associate with histopathological and genomic characteristics, and survival outcomes. Extensive stromal remodeling occurs in GAC progression. High SDC2 expression in cancer-associated fibroblasts (CAFs) is linked to aggressive phenotypes and poor survival, and SDC2 overexpression in CAFs contributes to tumor growth. Our study provides a high-resolution GAC TME atlas and underscores potential targets for further investigation.

Proteogenomic landscape of gastric adenocarcinoma peritoneal metastases.

Advanced gastric adenocarcinoma (GAC) often leads to peritoneal carcinomatosis (PC) and is associated with very poor outcome. Here we report the comprehensive proteogenomic study of ascites derived cells from a prospective GAC cohort (n = 26 patients with peritoneal carcinomatosis, PC). A total of 16,449 proteins were detected from whole cell extracts (TCEs). Unsupervised hierarchical clustering resulted in three distinct groups that reflected extent of enrichment in tumor cells. Integrated analysis revealed enriched biological pathways and notably, some druggable targets (cancer-testis antigens, kinases, and receptors) that could be exploited to develop effective therapies and/or tumor stratifications. Systematic comparison of expression levels of proteins and mRNAs revealed special expression patterns of key therapeutics target notably high mRNA and low protein expression of HAVCR2 (TIM-3), and low mRNA but high protein expression of cancer-testis antigens CTAGE1 and CTNNA2. These results inform strategies to target GAC vulnerabilities.

Blood-based Proteomic Signatures Associated With MEN1-related Duodenopancreatic Neuroendocrine Tumor Progression.

PURPOSE: Patients with multiple endocrine neoplasia type 1 (MEN1) are predisposed to develop duodenopancreatic neuroendocrine tumors (dpNETs), and metastatic dpNET is the primary cause of disease-related mortality. Presently, there is a paucity of prognostic factors that can reliably identify patients with MEN1-related dpNETS who are at high risk of distant metastasis. In the current study, we aimed to establish novel circulating molecular protein signatures associated with disease progression. EXPERIMENTAL DESIGN: Mass spectrometry-based proteomic profiling was conducted on plasmas procured through an international collaboration between MD Anderson Cancer Center, the National Institutes of Health, and the University Medical Center Utrecht from a cohort of 56 patients with MEN1 [14 with distant metastasis dpNETs (cases) and 42 with either indolent dpNETs or no dpNETs (controls)]. Findings were compared to proteomic profiles generated from serially collected plasmas from a mouse model of Men1-pancreatic neuroendocrine tumors (Men1fl/flPdx1-CreTg) and control mice (Men1fl/fl). RESULTS: A total of 187 proteins were found to be elevated in MEN1 patients with distant metastasis compared to controls, including 9 proteins previously associated with pancreatic cancer and other neuronal proteins. Analyses of mouse plasmas revealed 196 proteins enriched for transcriptional targets of oncogenic MYCN, YAP1, POU5F1, and SMAD that were associated with disease progression in Men1fl/flPdx1-CreTg mice. Cross-species intersection revealed 19 proteins positively associated with disease progression in both human patients and in Men1fl/flPdx1-CreTg mice. CONCLUSIONS: Our integrated analyses identified novel circulating protein markers associated with disease progression in MEN1-related dpNET.

A Nasal Inflammatory Cytokine Signature Is Associated with Early Graft-versus-Host Disease of the Lung after Allogeneic Hematopoietic Cell Transplantation: Proof of Concept.

Respiratory inflammation in bronchiolitis obliterans syndrome (BOS) after hematopoietic cell transplantation (HCT) is poorly understood. Clinical criteria for early-stage BOS (stage 0p) often capture HCT recipients without BOS. Measuring respiratory tract inflammation may help identify BOS, particularly early BOS. We conducted a prospective observational study in HCT recipients with new-onset BOS (n = 14), BOS stage 0p (n = 10), and recipients without lung impairment with (n = 3) or without (n = 8) chronic graft-versus-host disease and measured nasal inflammation using nasosorption at enrollment and then every 3 mo for 1 y. We divided BOS stage 0p into impairment that did not return to baseline values (preBOS, n = 6), or transient impairment (n = 4). We tested eluted nasal mucosal lining fluid from nasosorption matrices for inflammatory chemokines and cytokines using multiplex magnetic bead immunoassays. We analyzed between-group differences using the Kruskal-Wallis method, adjusting for multiple comparisons. We found increased nasal inflammation in preBOS and therefore directly compared patients with preBOS to those with transient impairment, as this would be of greatest diagnostic relevance. After adjusting for multiple corrections, we found significant increases in growth factors (FGF2, TGF-α, GM-CSF, VEGF), macrophage activation (CCL4, TNF-α, IL-6), neutrophil activation (CXCL2, IL-8), T cell activation (CD40 ligand, IL-2, IL-12p70, IL-15), type 2 inflammation (eotaxin, IL-4, IL-13), type 17 inflammation (IL-17A), dendritic maturation (FLT3 ligand, IL-7), and counterregulatory molecules (PD-L1, IL-1 receptor antagonist, IL-10) in preBOS patients compared to transient impairment. These differences waned over time. In conclusion, a transient multifaceted nasal inflammatory response is associated with preBOS. Our findings require validation in larger longitudinal cohorts.

Epithelial SOX9 drives progression and metastases of gastric adenocarcinoma by promoting immunosuppressive tumour microenvironment.

OBJECTIVE: Many cancers engage embryonic genes for rapid growth and evading the immune system. SOX9 has been upregulated in many tumours, yet the role of SOX9 in mediating immunosuppressive tumour microenvironment is unclear. Here, we aim to dissect the role of SOX9-mediated cancer stemness attributes and immunosuppressive microenvironment in advanced gastric adenocarcinoma (GAC) for novel therapeutic discoveries. METHODS: Bulk RNAseq/scRNA-seq, patient-derived cells/models and extensive functional studies were used to identify the expression and functions of SOX9 and its target genes in vitro and in vivo. Immune responses were studied in PBMCs or CD45+ immune cells cocultured with tumour cells with SOX9high or knockout and the KP-Luc2 syngeneic models were used for efficacy of combinations. RESULTS: SOX9 is one of the most upregulated SOX genes in GAC and highly expressed in primary and metastatic tissues and associated with poor prognosis. Depletion of SOX9 in patient-derived GAC cells significantly decreased cancer stemness attributes, tumour formation and metastases and consistently increased CD8+ T cell responses when cocultured with PBMCs/CD45+ cells from GAC patients. RNA sequencing identified the leukaemia inhibitory factor (LIF) as the top secreted molecule regulated by SOX9 in tumour cells and was enriched in malignant ascites and mediated SOX9-induced M2 macrophage repolarisation and inhibited T cell function. CONCLUSION: Epithelial SOX9 is critical in suppressing CD8+ T cell responses and modified macrophage function in GAC through the paracrine LIF factor. Cotargeting LIF/LIFR and CSF1R has great potential in targeting SOX9-mediated cancer stemness, T cell immunosuppression and metastases suggesting the novel combination therapy against advanced GAC.

Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types.

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss' Kappa score between-observers ranged from 0.31-0.50 and 0.55-0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61-0.66 and 0.70-0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice.

Contributions of Circulating microRNAs for Early Detection of Lung Cancer.

There is unmet need to develop circulating biomarkers that would enable earlier interception of lung cancer when more effective treatment options are available. Here, a set of 30 miRNAs, selected from a review of the published literature were assessed for their predictive performance in identifying lung cancer cases in the pre-diagnostic setting. The 30 miRNAs were assayed using sera collected from 102 individuals diagnosed with lung cancer within one year following blood draw and 212 controls matched for age, sex, and smoking status. The additive performance of top-performing miRNA candidates in combination with a previously validated four-protein marker panel (4MP) consisting of the precursor form of surfactant protein B (Pro-SFTPB), cancer antigen 125 (CA125), carcinoembryonic antigen (CEA) and cytokeratin-19 fragment (CYFRA21-1) was additionally assessed. Of the 30 miRNAs evaluated, five (miR-320a-3p, miR-210-3p, miR-92a-3p, miR-21-5p, and miR-140-3p) were statistically significantly (Wilcoxon rank sum test p < 0.05) elevated in case sera compared to controls, with individual AUCs ranging from 0.57−0.62. Compared to the 4MP alone, the combination of 3-miRNAs + 4MP improved sensitivity at 95% specificity by 19.1% ((95% CI of difference 0.0−28.6); two-sided p: 0.006). Our findings demonstrate utility for miRNAs for early detection of lung cancer in combination with a four-protein marker panel.

A Comprehensive Search of Non-Canonical Proteins in Non-Small Cell Lung Cancer and Their Impact on the Immune Response.

There is substantial interest in mining neoantigens for cancer applications. Non-canonical proteins resulting from frameshift mutations have been identified as neoantigens in cancer. We investigated the landscape of non-canonical proteins in non-small cell lung cancer (NSCLC) and their induced immune response in the form of autoantibodies. A database of cryptoproteins was computationally constructed and comprised all alternate open reading frames (altORFs) and ORFs identified in pseudogenes, noncoding RNAs, and untranslated regions of mRNAs that did not align with known canonical proteins. Proteomic profiles of seventeen lung adenocarcinoma (LUAD) cell lines were searched to evaluate the occurrence of cryptoproteins. To assess the immunogenicity, immunoglobulin (Ig)-bound cryptoproteins in plasmas were profiled by mass spectrometry. The specimen set consisted of plasmas from 30 newly diagnosed NSCLC cases, pre-diagnostic plasmas from 51 NSCLC cases, and 102 control plasmas. An analysis of LUAD cell lines identified 420 cryptoproteins. Plasma Ig-bound analyses revealed 90 cryptoproteins uniquely found in cases and 14 cryptoproteins that had a fold-change >2 compared to controls. In pre-diagnostic samples, 17 Ig-bound cryptoproteins yielded an odds ratio ≥2. Eight Ig-bound cryptoproteins were elevated in both pre-diagnostic and newly diagnosed cases compared to controls. Cryptoproteins represent a class of neoantigens that induce an autoantibody response in NSCLC.

Proteomic Profiling of the Tumor Microenvironment.

The tumor microenvironment forms a complex pro-tumorigenic milieu constituted by extracellular matrix, surrounding stroma, infiltrating cell populations, and signaling molecules. Proteomic studies have the potential to reveal how individual cell populations within the tumor tissue modulate the microenvironment through protein secretion and consequently alter their protein expression and localization to adapt to this milieu. As a result, proteomic approaches have uncovered how these dynamic components communicate and promote tumor development and progression. The characterization of these mechanisms is relevant for the identification of clinically targetable pathways and for the development of diagnostic tools. Here we describe a method based on the isolation of individual cell compartments and the chromatographic fractionation of intact proteins, followed by enzymatic digestion of individual fractions, and mass-spectrometry analysis, for the profiling of tumor microenvironment cell populations.

Blood-Based Biomarker Panel for Personalized Lung Cancer Risk Assessment.

PURPOSE: To investigate whether a panel of circulating protein biomarkers would improve risk assessment for lung cancer screening in combination with a risk model on the basis of participant characteristics. METHODS: A blinded validation study was performed using prostate lung colorectal ovarian (PLCO) Cancer Screening Trial data and biospecimens to evaluate the performance of a four-marker protein panel (4MP) consisting of the precursor form of surfactant protein B, cancer antigen 125, carcinoembryonic antigen, and cytokeratin-19 fragment in combination with a lung cancer risk prediction model (PLCOm2012) compared with current US Preventive Services Task Force (USPSTF) screening criteria. The 4MP was assayed in 1,299 sera collected preceding lung cancer diagnosis and 8,709 noncase sera. RESULTS: The 4MP alone yielded an area under the receiver operating characteristic curve of 0.79 (95% CI, 0.77 to 0.82) for case sera collected within 1-year preceding diagnosis and 0.74 (95% CI, 0.72 to 0.76) among the entire specimen set. The combined 4MP + PLCOm2012 model yielded an area under the receiver operating characteristic curve of 0.85 (95% CI, 0.82 to 0.88) for case sera collected within 1 year preceding diagnosis. The benefit of the 4MP in the combined model resulted from improvement in sensitivity at high specificity. Compared with the USPSTF2021 criteria, the combined 4MP + PLCOm2012 model exhibited statistically significant improvements in sensitivity and specificity. Among PLCO participants with ≥ 10 smoking pack-years, the 4MP + PLCOm2012 model would have identified for annual screening 9.2% more lung cancer cases and would have reduced referral by 13.7% among noncases compared with USPSTF2021 criteria. CONCLUSION: A blood-based biomarker panel in combination with PLCOm2012 significantly improves lung cancer risk assessment for lung cancer screening.

CES2 sustains HNF4α expression to promote pancreatic adenocarcinoma progression through an epoxide hydrolase-dependent regulatory loop.

OBJECTIVE: Intra-tumoral expression of the serine hydrolase carboxylesterase 2 (CES2) contributes to the activation of the pro-drug irinotecan in pancreatic ductal adenocarcinoma (PDAC). Given other potential roles of CES2, we assessed its regulation, downstream effects, and contribution to tumor development in PDAC. METHODS: Association between the mRNA expression of CES2 in pancreatic tumors and overall survival was assessed using The Cancer Genome Atlas. Cell viability, clonogenic, and anchorage-independent growth assays as well as an orthotopic mouse model of PDAC were used to evaluate the biological relevance of CES2 in pancreatic cancer. CES2-driven metabolic changes were determined by untargeted and targeted metabolomic analyses. RESULTS: Elevated tumoral CES2 mRNA expression was a statistically significant predictor of poor overall survival in PDAC patients. Knockdown of CES2 in PDAC cells reduced cell viability, clonogenic capacity, and anchorage-independent growth in vitro and attenuated tumor growth in an orthotopic mouse model of PDAC. Mechanistically, CES2 was found to promote the catabolism of phospholipids resulting in HNF4α activation through a soluble epoxide hydrolase (sEH)-dependent pathway. Targeting of CES2 via siRNA or small molecule inhibitors attenuated HNF4α protein expression and reduced gene expression of classical/progenitor markers and increased basal-like markers. Targeting of the CES2-sEH-HNF4α axis using small molecule inhibitors of CES2 or sEH reduced cell viability. CONCLUSIONS: We establish a novel regulatory loop between CES2 and HNF4α to sustain the progenitor subtype and promote PDAC progression and highlight the potential utility of CES2 or sEH inhibitors for the treatment of PDAC as part of non-irinotecan-containing regimens.

Combinatorial Effect of PLK1 Inhibition with Temozolomide and Radiation in Glioblastoma.

New strategies that improve median survivals of only ~15-20 months for glioblastoma (GBM) with the current standard of care (SOC) which is concurrent temozolomide (TMZ) and radiation (XRT) treatment are urgently needed. Inhibition of polo-like kinase 1 (PLK1), a multifunctional cell cycle regulator, overexpressed in GBM has shown therapeutic promise but has never been tested in the context of SOC. Therefore, we examined the mechanistic and therapeutic impact of PLK1 specific inhibitor (volasertib) alone and in combination with TMZ and/or XRT on GBM cells. We quantified the effects of volasertib alone and in combination with TMZ and/or XRT on GBM cell cytotoxicity/apoptosis, mitochondrial membrane potential (MtMP), reactive oxygen species (ROS), cell cycle, stemness, DNA damage, DNA repair genes, cellular signaling and in-vivo tumor growth. Volasertib alone and in combination with TMZ and/or XRT promoted apoptotic cell death, altered MtMP, increased ROS and G2/M cell cycle arrest. Combined volasertib and TMZ treatment reduced side population (SP) indicating activity against GBM stem-like cells. Volasertib combinatorial treatment also significantly increased DNA damage and reduced cell survival by inhibition of DNA repair gene expression and modulation of ERK/MAPK, AMPK and glucocorticoid receptor signaling. Finally, as observed in-vitro, combined volasertib and TMZ treatment resulted in synergistic inhibition of tumor growth in-vivo. Together these results identify new mechanisms of action for volasertib that provide a strong rationale for further investigation of PLK1 inhibition as an adjunct to current GBM SOC therapy.