Biomarkers In Oncology Research Articles

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294.

PurposeA magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

Cancer activation pathways of thymic epithelial tumors (TETs) by targeted gene expression analysis.

8575 Background: TETs are rare malignancies of the anterior mediastinum. Clinical behavior varies from mild thymoma (T) A to aggressive thymic carcinoma (TC). The biology of TETs is poorly understood and knowledge of the transcriptomic fingerprint of T and TC is limited. Additionally, up to 30% of patients (pts) will develop associated autoimmune disorders (AIDs). We aimed to characterize the main cancer activation pathways of the TET subgroups. Methods: We selected a representative balanced set of Ts and TCs to analyze 24 main cancer activation pathways using HTG Oncology biomarkers panel (2562 genes) by RNA sequencing. Tumor representative paraffin-embedded blocks were macrodissected for gene expression analysis. We analyzed epidemiologic, clinical and pathological characteristics of pts with TET’s and correlated with genes expression based on cancer Hallmarks. Results: From January 2010 to December 2019, 219 pts were included in the cohort. Molecular results of 194 pts were available. Median age at diagnosis was 56 (9-83) years. 54.1% were women. 65/194 (33.5%) reported AIDs. T B2 was the most frequent (n=41, 21.1%), followed by B1, AB, B3, TC and A. RNA expression analysis identified 2 main clusters, corresponding mainly to T (cluster 2) and TC (cluster 1) respectively (p<0.0001) (Table). Tumors of cluster 1 (TCs predominant) shown activated pathways (MYC [gene ratio= 0.5]; p<0.0001). In cluster 2 (T predominant), activated pathways differed among subgroups: B1 (E2F[0.5], G2M checkpoint [0.45]; p<0.001), B2 (E2F [>0.4]; p<0.0001). Routes were mostly suppressed: A (MYC [>0.5], E2F[>0.4], G2M checkpoint[>0.45], mitotic spindle[>0.35], MTOR [<0.35]; p<0.001), AB (INFα [>0.5], inflammatory response [>0.45], INTɣ [0.45], NFkb [>0.4], MTOR[>0.4]; p<0.001), B1 (EMT [0.6], angiogenesis [>0.5], INFα [0.5], homeostasis [0.5], NFkb [0.5], INTɣ [>0.45], myogenesis [<0.4]; p<0.0001), B2 (INFα [>0.65], INTɣ [>0.5], NFkb [0.5], EMT [0.45], inflammatory response [<0.4]; p< 0.0001), B3 (EMT [0.6], MYC [0.45]; p<0.001). Among pts reporting AIDs 61 and 4 were associated to cluster 2 and 1, respectively (p=0.017). Conclusions: We describe differential molecular characteristics among histological subgroups in 2 clusters. The analysis suggests new therapeutic venues. Additional analysis will be presented on outliers and response to treatment.[Table: see text]

Subgroup of post-neoadjuvant luminal-B tumors assessed by HTG in PENELOPE-B investigating palbociclib in high risk HER2-/HR+ breast cancer with residual disease.

519 Background: About one third of patients with hormone-receptor-positive (HR+), HER2‐ primary breast cancer with residual invasive disease after neoadjuvant chemotherapy will relapse despite adjuvant endocrine therapy. Therapeutic inhibition of cyclin-dependent kinase 4 and 6 (CDK 4/6) by palbociclib combined with endocrine therapy demonstrated highly relevant efficacy in metastatic breast cancer. The phase III PENELOPE-B (NCT01864746) study did not show a significant benefit from palbociclib in women with centrally confirmed HR+, HER2- primary breast cancer without a pathological complete response after taxane‐containing neoadjuvant chemotherapy and at high-risk of relapse (CPS‐EG score ≥3 or 2 and ypN+) for the primary endpoint (Loibl et al. JCO 2021). Methods: After completion of neoadjuvant chemotherapy and locoregional therapy, PENELOPE-B patients were randomized (1:1) to receive 13 cycles (1 year) of palbociclib 125mg daily or placebo on days 1-21 in a 28d cycle in addition to standard endocrine therapy. Analysis of the primary endpoint of invasive disease-free survival (iDFS) was planned after 290 events. Secondary objective included iDFS in luminal-B group by treatment. Gene expression in post-neoadjuvant surgical residual tumor tissue samples was profiled using the HTG EdgeSeq Oncology Biomarker Panel targeting 2559 genes (HTG Molecular Diagnostics Inc.). Based on 91 genes of this panel the AIMS subtype (Paquet & Hallett, JNCI 2014) was calculated. Results: Gene expressions were measured in tumors from 906 of 1250 (72%) PENELOPE-B patients; 663 had LumA subtype, 64 LumB, 135 NormL, 16 BasalL, and 28 HER2E. Compared to LumA the LumB patients were older, had higher post-neoadjuvant Ki-67, higher risk status (CPS-EG), and higher grade; no significant correlation was found for the region of participating sites, cT, ypT, and ypN. Patients with LumB tumors had an estimated 3-year iDFS of 71.9% with palbociclib vs 44.8% with placebo HR = 0.50 (0.24-1.05); outcome was similar in patients with LumA tumors (3-year iDFS 83.9% vs 79.5%, HR = 0.93 (0.68-1.28), interaction p = 0.132); this was confirmed in multivariable analyses. Ki-67 by IHC and proliferation biomarkers from the HTG panel also showed no significant interaction with treatment. Conclusions: PENELOPE-B did not show a benefit from the addition of 1 year palbociclib to endocrine therapy compared to placebo in the total enrolled high-risk primary breast cancer population. However, the small group of luminal-B tumors (n = 64) derived benefit from palbociclib, although without a statistically significant interaction. Further investigation is required in a larger cohort to validate a palbociclib benefit that might be confined to this group.

CCNE1 mRNA and cyclin E1 protein expression as predictive biomarkers for efficacy of palbociclib plus fulvestrant versus capecitabine in the phase III PEARL study.

1014 Background: The randomized PEARL trial found no superiority of palbociclib plus endocrine therapy over capecitabine in patients (pts) with metastatic HR-positive, HER2-negative breast cancer resistant to prior aromatase inhibitors (Martin M, Ann Oncol 2020). Gene expression analysis showed high CCNE1 mRNA ( CCNE1) conferring relative resistance to palbociclib in the PALOMA-3 trial (Turner N, JCO 2019), but further validation is needed. Cyclin E1 protein (cyclin E1) expression in this context has not been studied in randomized trials. We explored CCNE1 and cyclin E1 as predictive biomarkers in tumor samples from the PEARL study. Methods: Formalin-fixed paraffin-embeded tumor samples were retrieved from pts enrolled in PEARL cohort 2 (palbociclib (PAL) + fulvestrant (FUL) vs capecitabine (CAPE)). We measured CCNE1 using the HTG EdgeSeq Oncology Biomarker Panel (HTG Molecular Diagnostics). Cyclin E1 immunohistochemistry (IHC) staining was performed using specific mouse monoclonal antibody HE12 (Abcam) and scored as percentage of invasive nuclei stained (0-100%). CCNE1 and cyclin E1 correlations were explored using Pearson coefficients. Cox regression models were used for progression free-survival (PFS) analyses using expression levels split by median, to define high ( > median values) vs. low expression. Site of disease and prior chemotherapy were used as confounders in multivariate models. Results: Analyses were conducted in 219 pts (47% receiving PAL + FUL and 53% CAPE) with available tumors, with the analysed patients representative of the overall study. Most samples were from the archival primary (72%), obtained > 5 years before this analysisº (74%). CCNE1 and cyclin E1 were only moderately correlated (r = 0.5). Median CCNE1 was higher in metastatic vs primary (7.37 vs 6.94, p < 0.01), and in luminal B and non-luminal subtypes compared to luminal A (p < 0.001). In patients with high CCNE1 expression, median PFS on CAPE was 10.35 and PAL + FUL was 5.68 (HR = 1.63, 95% CI 1.02-2.59, p = 0.042). In patients with low CCNE1 expression, median PFS on CAPE was 9.43 and PAL + FUL was 8.97 (adjusted HR = 0.93, 95% CI 0.59-1.48, p = 0.762, interaction p = 0.072). Median cyclin E1 protein was higher in luminal B and non-luminal subtypes compared to luminal A (p < 0.01). Cyclin E1 protein expression was not predictive of treatment effect (high cyclin E1 expression CAPE vs PAL + FUL HR = 1.17, low cyclin E1 expression CAPE vs PAL + FUL HR = 1.21, interaction p = 0.977). Conclusions: High tumor CCNE1 mRNA expression identified patients with relative resistance to palbociclib plus fulvestrant, validating prior observations although without statistical significance for interaction. Assessment of Cyclin E1 protein expression did not show predictive value. Investigation treatments to enhance CDK4/6 inhibitor efficacy in tumors with high CCNE1 expression is warranted. Clinical trial information: NCT02028507 .

MamaPred: A new and innovative approach to determine recurrence risk in HR+/HER2- early-stage breast cancer using HTG EdgeSeq technology.

558 Background: Genomic platforms, such as Mammaprint (Agendia) (MP) and OncoType (Genomic Health) (OT), have been validated to determine the risk of relapse in therapeutic decision-making in early-stage hormone receptor positive (HR+), epidermal growth factor receptor 2 (HER2) negative breast cancer (BC). Discordances in risk allocation between these platforms affect up to 30% of patients. This study aims to develop the MamaPred test to improve the diagnostic performance of recurrence risk in HR+/HER2- early-stage BC. Methods: A total of 606 HR+/HER2- early-stage BC previously tested with OT [n = 287; Low Risk (LR) = 165, Intermediate Risk (IR) = 103 and High Risk (HR) = 19] and MP (n = 319; LR = 217 and HR = 102) were included. A retrospective independent series of 144 HR+/HER2- early-stage BC [median follow-up: 10.53 years (range: 3.1-23.1 yrs); age (median = 62.9 yrs (33-89 yrs); systemic relapse 10.5% (n = 15)] was used as validation set.The expression levels of 2560 cancer-related mRNAs were evaluated from one 5 μm thin-section of a FFPE block (15 mm2 tumor area) using the Oncology Biomarker Panel (OBP) and the HTG EdgeSeq System (HTG Molecular Diagnostics. Inc) and quantified by NGS on a NextSeq550 sequencer (Illumina). A predictive model was built from normalized and logarithmically transformed values (rescaled to [0, 1]) using as response a binary meta-variable constructed by taking the values -1 (for LR of MP and OT together the OT IR) and 1 (for HR MP and OT). Differential expression, GSEA and visualization were performed with DESeq2, gage and pathview packages respectively in R v4.0.1. Results: MamaPred consists of a logistic regression classifier with an elastic net penalty (mix of L1 and L2 priors as regularizer) where the mixing parameter is optimized along with regularization strength by selecting the ones that minimize the area under the precision and recall curve over a validation split for each training fold. Metrics of MamaPred were: balanced accuracy, 80.5%; Kappa, 0.562; specificity, 80.7%; and NPV, 91.4%. GSE analysis on differentially expressed genes (q < 0.1) showed four KEGG pathways overrepresented in HR (p < 0.05): adherens junction, tight junction, glutathione metabolism and focal adhesion; and two underrepresented: DNA replication (p = 0.0765) and pyrimidine metabolism (p = 0.086).The prognostic prediction of MamaPred was validated on the independent retrospective series, distant disease-free survival for HR and LR being 88.63% (95% IC: 78.72%-99.78%) and 98.1% (95% IC: 95.6%-100%) respectively (p = 0.00603). Correlation between the probabilities assigned to any given sample and its replicas was extremely high (r > 0.9 p < 1e-5). Conclusions: MamaPred identifies HR+/HER2- early-stage BC patients with high-risk of distant relapse improving the prognostic value of those studies that compare MP and OT, suggesting a more precise risk classification.

Cancer Stem Cell Marker CD44 Plays Multiple Key Roles in Human Cancers: Immune Suppression/Evasion, Drug Resistance, Epithelial-Mesenchymal Transition, and Metastasis.

One of the most frequently utilized cancer stem cell markers in human cancers, including colorectal cancer and breast cancer, is CD44. A glycoprotein, CD44, traverses the cell membrane and binds to many ligands, including hyaluronan, resulting in activation of signaling cascades. There are conflicting data, however, on expression of CD44 in relationship to subtypes of cancers. Moreover, the associations of CD44 expression with drug resistance, immune infiltration, epithelial-mesenchymal transition (EMT), metastasis, and clinical prognosis in several cancer types are not clear and call for further studies. We report here an original study on CD44 expression in several human cancers and its relationship with tumorigenesis. We harnessed data from the publicly available databases, including The Cancer Genome Atlas, Gene Expression Profiling Interactive Analysis, Oncomine, Genomics of Drug Sensitivity in Cancer, and the Tumor Immune Estimation Resource. Our analysis reveals that CD44 expression varies across cancer types and is significantly associated with cancer patients' survival, in gastric and pancreatic cancers (p < 0.05). In addition, CD44 expression is closely linked with immune infiltration and immune suppressive features in pancreatic, colon adenocarcinoma, and stomach cancer. High CD44 expression was significantly correlated with the expression of drug resistance, EMT, and metastasis associated genes. Tumors expressing high CD44 have higher mutation burden and afflict older patients compared to tumors expressing low CD44. Cell lines expressing high CD44 are more resistant to anticancer drugs compared to those expressing low CD44. Protein-protein interaction investigations and functional enrichment analysis showed that CD44 interacts with gene products related to cell-substrate adhesion, migration, platelet activation, and cellular response to stress. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that these genes play key roles in biological adhesion, cell component organization, locomotion, G-α-signaling, and the response to stimulus. In summary, these findings lend evidence for the multiple key roles played by CD44 in tumorigenesis and suggest that CD44 is considered further in future studies of cancer pathogenesis and the search for novel molecular targets and personalized medicine biomarkers in clinical oncology.

Surface-Enhanced Raman Scattering (SERS) Spectroscopy for Sensing and Characterization of Exosomes in Cancer Diagnosis.

Simple SummaryThe distinct molecular and biological properties of exosomes, together with their abundance and stability, make them an ideal target in liquid biopsies for early diagnosis and disease monitoring. On the other hand, in recent years, nanomaterial-based optical biosensors have been extensively investigated as novel, rapid and sensitive tools for exosome detection and discrimination. The scope of this review is to summarize and coherently discussed the diverse applications, challenges and limitations of nanosensors based on surface-enhanced Raman spectroscopy (SERS) as the optosensing technique.Exosomes are emerging as one of the most intriguing cancer biomarkers in modern oncology for early cancer diagnosis, prognosis and treatment monitoring. Concurrently, several nanoplasmonic methods have been applied and developed to tackle the challenging task of enabling the rapid, sensitive, affordable analysis of exosomes. In this review, we specifically focus our attention on the application of plasmonic devices exploiting surface-enhanced Raman spectroscopy (SERS) as the optosensing technique for the structural interrogation and characterization of the heterogeneous nature of exosomes. We summarized the current state-of-art of this field while illustrating the main strategic approaches and discuss their advantages and limitations.

O29: PREDICTING RESPONSE TO NEOADJUVANT THERAPY IN OESOPHAGEAL ADENOCARCINOMA PRE-TREATMENT BIOPSIES

Abstract Aims We currently cannot predict which patients with locally advanced oesophageal adenocarcinoma will be amongst the 15-20% to gain a clinically important response to neoadjuvant therapy (NAT). This pilot study aimed to identify differentially expressed genes from oesophageal adenocarcinoma pre-treatment biopsies between responders and non-responders to NAT and develop methodology for predicting response. Method Response to NAT was assessed pathologically using Tumour Regression Grading (TRG). Pre-treatment formalin-fixed paraffin embedded samples were analysed with two nuclease protection assays (EdgeSeq, HTG = Oncology Biomarker Panel (OBP) and Precision Immuno-Oncology Panel (PIP)). Sequencing was performed on the NextSeq500 (Illumina). Result Whilst there was no difference in pre-treatment characteristics, responders (TRG1-2, n=26) had significantly better post-treatment pathology and overall survival than non-responders (TRG4-5, n=30). Genes up-regulated in responders were involved in regulating cell cycling, whereas genes up-regulated in non-responders were involved in cytokine signalling and the immune response. Neuronal artificial network models could predict response to NAT with overall accuracy of 73% and 68% for the OBP and PIP, respectively, which is promising considering the small sample size. As no model will be 100% accurate, we developed a model that could take patient's views into consideration with an adjustable probability threshold for classification. Conclusion This pilot study informs a biologically sound hypothesis for the basis of response to NAT and suggests prediction from pre-treatment biopsies may be possible using EdgeSeq. We now aim to validate these results in a larger study to inform a bespoke classifier of response to enable delivery of precision therapy. Take-home message In oesophageal adenocarcinoma, responders and non-responders to neoadjuvant therapy have different expression profiles. Through using EdgeSeq in larger studies, we may be able to predict which patients will respond to treatment, allowing for delivery of precision therapy.

Identification of Tumor-Specific MRI Biomarkers Using Machine Learning (ML).

The identification of reliable and non-invasive oncology biomarkers remains a main priority in healthcare. There are only a few biomarkers that have been approved as diagnostic for cancer. The most frequently used cancer biomarkers are derived from either biological materials or imaging data. Most cancer biomarkers suffer from a lack of high specificity. However, the latest advancements in machine learning (ML) and artificial intelligence (AI) have enabled the identification of highly predictive, disease-specific biomarkers. Such biomarkers can be used to diagnose cancer patients, to predict cancer prognosis, or even to predict treatment efficacy. Herein, we provide a summary of the current status of developing and applying Magnetic resonance imaging (MRI) biomarkers in cancer care. We focus on all aspects of MRI biomarkers, starting from MRI data collection, preprocessing and machine learning methods, and ending with summarizing the types of existing biomarkers and their clinical applications in different cancer types.

A miRNA signature predicts benefit from addition of hypoxia-modifying therapy to radiation treatment in invasive bladder cancer

BackgroundmiRNAs are promising biomarkers in oncology as their small size makes them less susceptible to degradation than mRNA in FFPE tissue. We aimed to derive a hypoxia-associated miRNA signature for bladder cancer.MethodsTaqman miRNA array cards identified miRNA seed genes induced under hypoxia in bladder cancer cell lines. A signature was derived using feature selection methods in a TCGA BLCA training data set. miRNA expression data were generated for 190 tumours from the BCON Phase 3 trial and used for independent validation.ResultsA 14-miRNA hypoxia signature was derived, which was prognostic for poorer overall survival in the TCGA BLCA cohort (n = 403, p = 0.001). Univariable analysis showed that the miRNA signature predicted an overall survival benefit from having carbogen–nicotinamide with radiotherapy (HR = 0.30, 95% CI 0.094–0.95, p = 0.030) and performed similarly to a 24-gene mRNA signature (HR = 0.47, 95% CI 0.24–0.92, p = 0.025). Combining the signatures improved performance (HR = 0.26, 95% CI 0.08–0.82, p = 0.014) with borderline significance for an interaction test (p = 0.065). The interaction test was significant for local relapse-free survival LRFS (p = 0.033).ConclusionA 14-miRNA hypoxia signature can be used with an mRNA hypoxia signature to identify bladder cancer patients benefitting most from having carbogen and nicotinamide with radiotherapy.

Cross-platform comparison of immune-related gene expression to assess intratumor immune responses following cancer immunotherapy

Neoadjuvant immunotherapy can induce immune responses within the tumor microenvironment. Gene expression can be used to assess responses with limited amounts of conventionally-fixed patient-derived samples. We aim to assess the cross-platform concordance of immune-related gene expression data. We performed comparisons across three panels in two platforms: Nanostring nCounter® PanCancer Immune Profiling Panel (nS), HTG EdgeSeq Oncology Biomarker Panel (HTG OBP) and Precision Immuno-Oncology Panel (HTG PIP). All tissue samples of 14 neoadjuvant GM-CSF treated, 14 neoadjuvant Provenge treated, and 12 untreated prostate cancer patients were radical prostatectomy (RP) tissues, while 6 prostatitis patients and 6 non-prostatitis subjects were biopsies. For all 52 patients, more than 90% of the common genes were significantly correlated (p < 0.05) and more than 76% of the common genes were highly correlated (r > 0.5) between any two panels. Co-inertia analysis also demonstrated high overall dataset structure similarity (correlation>0.84). Although both dimensionality reduction visualization analysis and unsupervised hierarchical cluster analysis for highly correlated common genes (r > 0.9) suggested a high-level of consistency across the panels, there were subsets of genes that were differentially expressed across the panels. In addition, while the effect size of the differential testing for neoadjuvant treated vs. untreated localized prostate cancer patients across the panels were significantly correlated, some genes were only differentially expressed in the HTG panels. Finally, the HTG PIP panel had the best classification performance among the 3 panels. These differences detected may be a result of the different panels or platforms due to their technical setting and focus. Thus, researchers should be aware of those potential differences when deciding which platform and panel to use.

International Liver Cancer Association (ILCA) White Paper on Biomarker Development for Hepatocellular Carcinoma

International Liver Cancer Association (ILCA) White Paper on Biomarker Development for Hepatocellular Carcinoma

Abstract PS2-01: Plk1 expression &amp; efficacy of palbociclib in advanced hormonal receptor-positive breast cancer patients from PEARL study (GEICAM 2012-03)

Abstract Background: CDK 4/6 inhibitors (CDK 4/6i) with endocrine therapy (ET) combination therapy have improved outcomes in patients (pts) with hormonal receptor positive (HR+)/human epidermal growth factor receptor negative (HER2-) advanced breast cancer (ABC). However, most pts eventually develop resistance to these drugs, and one third never respond. Aside from HR positivity, predictive markers of clinical benefit from CDK 4/6i remains elusive. We aimed to identify biomarkers of response to palbociclib (PAL) and analyze potential therapeutic targets to reverse resistance. Methods: PEARL trial is a multicenter phase 3 study that assigned 601 postmenopausal HR+/HER2- ABC pts, whose disease progressed on aromatase inhibitors (AIs), to receive PAL + ET vs capecitabine (CAPE). We performed a differential gene expression analysis in pre-treatment tumors in extreme responders to PAL using the HTG EdgeSeq Oncology Biomarker Panel (HTG Molecular Diagnostics, Inc.), containing 2534 cancer related genes. Samples were subset in 2 categories: refractory (progressive disease as best response) vs sensitive (progression-free survival (PFS) within the upper quartile). Cox regression and Significance Analysis of Microarrays (SAM) analysis adjusting for multiple comparisons were performed. Results: We analyzed 455 (75.7%) pts with pre-treatment tumors available [from them, PAL + ET arm: 229 (50.3%) pts; CAPE arm: 226 (49.7%) pts]. Fifty genes (false discovery rate (FDR)&amp;lt;0.05) were differentially expressed in pts sensitive vs refractory to PAL (E2F target genes, epithelial-to-mesenchymal transition (EMT) and cell cycle genes, mainly). Unsupervised hierarchical clustering of pts based on the expression of these genes revealed two clusters. Cluster 1 is composed mostly of resistant tumors, highly proliferative (Ki67≥20%: 70%) with a great proportion of luminal B (59%) and non-luminal tumors (19%). Cluster 2 is composed of sensitive, low proliferative (Ki67&amp;lt;20%: 58%), mostly luminal A tumors (75%). There was no difference in ESR1 mutations distribution between the two clusters (Table 1). Forty genes were up-regulated and associated with resistance, including CCNE1 and PLK1 (Polo Like Kinase 1). In the whole cohort, pts with high levels (&amp;gt; median) of PLK1 (PLK1-high) treated with PAL, had a worse PFS in a multivariate model (5.7 months (m) vs 9.3 m of median PFS in PLK1-High vs -Low; HR=1.64, 95% CI (1.25-2.34), p=0.0008; adjusted model for confounders: age, site of disease, sites of metastasis, prior chemotherapy and Ki67). There were no differences in population treated with CAPE (9.9 m vs 9.4 m, PLK1-High vs -Low; HR=0.82, 95% CI (0.56-1.21), p=0.3189). In the METABRIC cohort, PLK1-High was associated with worse overall survival in HR+/HER2- BC but not in triple negative nor in HER2+ tumors. Among HR+/HER2- tumors, PLK1 expression was higher in luminal B and HER2-enriched intrinsic subtypes. We interrogated DepMap database and found that in BC cells lines there was an inverse correlation between PLK1 expression and effect on cell viability of CDK4 CRISPR knock-out (Pearson correlation r:0.54, p=0.009), but not of CDK6 knock-out. Also, HR+/HER2-/High Ki67 BC cell lines (HCC1428, EFM19 and MCF7) showed resistance to PAL on cell proliferation assays but sensitivity to the PLK1 inhibitor BI-2536. Conclusion: High expression of PLK1 is associated with intrinsic resistance to PAL and ET, this might be overcome with PLK1 inhibition. Table 1PATIENT CHARACTERISTICSCluster 1Cluster 2ALLn=57n=47n=104RespondersSensitive42 (73.68%)14 (29.79%)56 (53.85%)Refractory15 (26.32%)33 (70.21%)48 (46.15%)ESR1Mutated9 (15.79%)13 (27.66%)22 (21.15%)Wild type45 (78.95%)34 (72.34%)79 (75.96%)Unknown3 (5.26%)0 (0%)3 (2.88%)PriorQTN42 (73.68%)31 (65.96%)73 (70.19%)Y15 (26.32%)16 (34.04%)31 (29.81%)SubtypeLumA43 (75.44%)10 (21.28%)53 (50.96%)LumB14 (24.56%)28 (59.57%)42 (40.38%)Non Luminal0 (0%)9 (19.15%)9 (8.65%)MetastasisOne21 (36.84%)15 (31.91%)36 (34.62%)Multiple36 (63.16%)32 (68.09%)68 (65.38%)KI67 20%KI67&amp;lt;2033 (57.89%)7 (14.89%)40 (38.46%)KI67≥2016 (28.07%)33 (70.21%)49 (47.12%)Unknown8 (14.04%)7 (14.89%)15 (14.42%)Objective ResponseComplete1 (1.75%)0 (0%)1 (0.96%)Partial16 (28.07%)6 (12.77%)22 (21.15%)Progressive15 (26.32%)33 (70.21%)48 (46.15%)Stable25 (43.86%)8 (17.02%)33 (31.73%) Citation Format: Angel Guerrero- Zotano, Christoph Zielinski, Miguel Gil-Gil, Manuel Ruiz-Borrego, Eva M. Ciruelos, Montserrat Munoz, Begoña Bermejo, Mireia Margeli, Antonio Antón, Tibor Csöszi, Andrés García-Palomo, Ana Santaballa, Jose Luis Alonso, Antonio Fernández, Massimo Corsaro, Jesús Herranz, Paula López, Rosalia Caballero, Christiane Thallinger, Miguel Martin. Plk1 expression &amp; efficacy of palbociclib in advanced hormonal receptor-positive breast cancer patients from PEARL study (GEICAM 2012-03) [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr PS2-01.

Circulating tumor DNA is detectable in canine histiocytic sarcoma, oral malignant melanoma, and multicentric lymphoma

Circulating tumor DNA (ctDNA) has become an attractive biomarker in human oncology, and its use may be informative in canine cancer. Thus, we used droplet digital PCR or PCR for antigen receptor rearrangement, to explore tumor-specific point mutations, copy number alterations, and chromosomal rearrangements in the plasma of cancer-affected dogs. We detected ctDNA in 21/23 (91.3%) of histiocytic sarcoma (HS), 2/8 (25%) of oral melanoma, and 12/13 (92.3%) of lymphoma cases. The utility of ctDNA in diagnosing HS was explored in 133 dogs, including 49 with HS, and the screening of recurrent PTPN11 mutations in plasma had a specificity of 98.8% and a sensitivity between 42.8 and 77% according to the clinical presentation of HS. Sensitivity was greater in visceral forms and especially related to pulmonary location. Follow-up of four dogs by targeting lymphoma-specific antigen receptor rearrangement in plasma showed that minimal residual disease detection was concordant with clinical evaluation and treatment response. Thus, our study shows that ctDNA is detectable in the plasma of cancer-affected dogs and is a promising biomarker for diagnosis and clinical follow-up. ctDNA detection appears to be useful in comparative oncology research due to growing interest in the study of natural canine tumors and exploration of new therapies.

Immunotherapy in Breast Cancer Patients: A Focus on the Use of the CurrentlyAvailable Biomarkers in Oncology

Immune checkpoint inhibitors (ICIs) have remarkably modified the way solid tumors are managed, including breast cancer. Unfortunately, only a relatively small number of breast cancer patients significantly respond to these treatments. To maximize the immunotherapy benefit in breast cancer, several efforts are currently being put forward for the identification of i) the best therapeutic strategy (i.e. ICI monotherapy or in association with chemotherapy, radiotherapy, or other drugs); ii) the optimal timing for administration (e.g. early/advanced stage of disease; adjuvant/neoadjuvant setting); iii) the most effective and reliable predictive biomarkers of response (e.g. tumor-infiltrating lymphocytes, programmed death-ligand 1, microsatellite instability associated with mismatch repair deficiency, and tumor mutational burden). In this article, we review the impacts and gaps in the characterization of immune-related biomarkers raised by clinical and translational research studies with immunotherapy treatments. Particular emphasis has been put on the documented evidence of significant clinical benefits of ICI in different randomized clinical trials, along with preanalytical and analytical issues in predictive biomarkers pathological assessment.

Age-stratified reference intervals unlock the clinical potential of circulating cell-free DNA as a biomarker of poor outcome for healthy individuals and patients with colorectal cancer.

Circulating cell‐free DNA (cfDNA) has spurred much interest as a biomarker in oncology. However, inter‐ and intra‐individual cfDNA levels vary greatly. Consequently, in order to base clinical decisions on cfDNA measurements, normal reference intervals are essential to avoid that ordinary variation is confused with clinically relevant change. The lack of reference intervals may potentially explain the ambiguous results reported in the field. Our study aimed to establish reference intervals and to evaluate the association between cfDNA and demographic and clinical variables, including colorectal cancer (CRC). Plasma samples and clinical data from 2817 subjects were collected including 1930 noncancer individuals and 887 CRC patients. cfDNA was measured using droplet digital polymerase chain reaction (PCR). The large cohort combined with robust cfDNA quantification enabled establishment of reference intervals (<67 years: 775‐4860 copies/mL; ≥67 years: 807‐6561 copies/mL). A cfDNA level above the age‐stratified 90% percentile was prognostic of reduced survival in both noncancer individuals and CRC patients, with HR values of 2.56 and 2.01, respectively. Moreover, cfDNA levels increased significantly with age, elevated BMI and chronic diseases. In CRC, the cfDNA level was increased for Stage IV, but not Stage I to Stage III cancer. In summary, the use of reference intervals revealed that high cfDNA levels were predictive of shorter survival in both noncancer individuals and CRC patients, and that CRC development did not affect the cfDNA level until metastatic dissemination. Furthermore, cfDNA levels were impacted by age and chronic diseases. Conclusively, our study presents reference intervals that will help pave the way for clinical utilization of cfDNA.

Discovery of novel DNA methylation biomarkers for non-invasive sporadic breast cancer detection in the Latino population.

Human diversity is one of the main pitfalls in the development of robust worldwide biomarkers in oncology. Epigenetic variability across human populations is associated with different genetic backgrounds, as well as variable lifestyles and environmental exposures, each of which should be investigated. To identify potential non-invasive biomarkers of sporadic breast cancer in the Uruguayan population, we studied genome-wide DNA methylation using Illumina methylation arrays in leukocytes of 22 women with sporadic breast cancer and 10 healthy women in a case-control study. We described a panel of 38 differentially methylated CpG positions that was able to cluster breast cancer patients (BCP) and controls, and that also recapitulated methylation differences in 12 primary breast tumors and their matched normal breast tissue. Moving forward, we simplified the detection method to improve its applicability in a clinical setting and used an independent well-characterized cohort of 80 leukocyte DNA samples from BCP and 80 healthy controls to validate methylation results at specific cancer-related genes. Our investigations identified methylation at CYFIP1 as a novel epigenetic biomarker candidate for sporadic breast cancer in the Uruguayan population. These results provide a proof-of-concept for the design of larger studies aimed at validating biomarker panels for the Latin American population.

Analysis of Adct-602 Pre-Clinical Activity in B-Cell Lymphoma Models and Identification of Potential Biomarkers for Its Activity

Analysis of Adct-602 Pre-Clinical Activity in B-Cell Lymphoma Models and Identification of Potential Biomarkers for Its Activity

Managing Deviating EQA Results: A Survey to Assess the Corrective and Preventive Actions of Medical Laboratories Testing for Oncological Biomarkers.

Laboratories testing predictive biomarkers in lung and colorectal cancer are advised to participate in external quality assessment (EQA) schemes. This study aimed to investigate which corrective actions were taken by laboratories if predetermined performance criteria were not met, to ultimately improve current test practices. EQA participants from the European Society of Pathology between 2014 and 2018 for lung and colorectal cancer were contacted, if they had at least one analysis error or test failure in the provided cases, to complete a survey. For 72.4% of 514 deviating EQA results, an appropriate action was performed, most often including staff training (15.2%) and protocol revisions (14.6%). Main assigned persons were the molecular biologist (40.0%) and pathologist (46.5%). A change in test method or the use of complex techniques, such as next-generation sequencing, required more training and the involvement of dedicated personnel to reduce future test failures. The majority of participants adhered to ISO 15189 and implemented suitable actions by designated staff, not limited to accredited laboratories. However, for 27.6% of cases (by 20 laboratories) no corrective action was taken, especially for pre-analytic problems and complex techniques. The surveys were feasible to request information on results follow-up and further recommendations were provided.

Urinary-Based Markers for Bladder Cancer Detection

Background The use of urine markers for diagnosis and surveillance has been a topic of broad interest and ongoing controversies in the management of patients with bladder cancer. There has been a constant quest for markers that demonstrate clinical utility. Aim In the framework of the International Consultation on Urological Diseases 2019 on Molecular Biomarkers in Urologic Oncology, a comprehensive review of literature on urinary biomarkers for bladder cancer has been performed. Results Currently available urinary markers include protein-based markers, RNA-based markers, and DNA-based markers. The introduction of high-throughput analysis technologies provides the opportunity to assess multiple parameters within a short period of time, which is of interest for RNA-based, DNA-based, and protein-based marker systems. A comprehensive analysis of molecular alterations in urine samples of bladder cancer patients may be of interest not only for diagnosis and surveillance but also for non-invasive longitudinal assessment of molecular, potentially therapy-relevant, alterations. However, most systems lack prospective validation within well-designed trials and have not been broadly implemented in daily clinical practice. Conclusions Because of limited data from prospective trials, the routine use of any urine marker except cytology is not considered as standard of care in international guidelines. There is an urgent need for prospective trials of urine markers to answer specific clinical questions.