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Breast cancer (BC) is the most frequent neoplasia affecting women worldwide normally detected at early stages. In this regard, early diagnosis drastically decreases mortality, however, around 20% of these patients will later relapse. This is mainly caused by undetectable molecular residual disease (MRD) not eliminated by standard primary treatments. Therefore, it is crucial to detect the after-treatment MRD to stratify the patients by their risk of relapse. Liquid biopsies have emerged as non-invasive method to obtain information about tumors and improve clinical cancer management. Regarding this, much has been hypothesized about utilizing high blood volumes to overcome the necessity of complex and resource-intensive next generation sequencing (NGS) methodologies to detect highly diluted blood tumor components in localized cancers. Herein, we employed a combined analysis of circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) together with high blood volumes and single-assay droplet digital PCR (ddPCR) to detect MRD with ultra-high sensitivity. We prospectively assayed 124 samples extracted at baseline, post-neoadjuvant therapy (NAT), post-surgery and a follow-up on a six-monthly basis. A median of 76.40 mL of blood to detect CTCs and 40 mL of plasma to detect ctDNA per patient from 19 BC women were used in this study. ddPCR assays were performed with a median of 14 partitions per determination to detect ctDNA and 12 partitions for CTCs. Overall, ctDNA, CTCs and ctDNA and/or CTCs were detected in 84.21%, 66.66% and 89.47% respectively in the pre-treatment blood samples. MRD (ctDNA and/or CTCs) was detected in 73.68% of the after NAT blood samples. On the other hand, it was detected in 46.66% and 70.00% of the post-surgery and follow-up samples respectively. Post-NAT MRD was detected in 57.14% (4/7) and 83.33% (10/12) of patients with and without pathological complete response pCR respectively. To note, the discordant patients achieving pCR in tissue with detectable MRD in blood were high-risk BC. Importantly, in one of the two patients without pCR and no MRD detected, not enough sample were available to complete the analysis. The other discordant patient presented a localized disease with residual cancer burden value of 1 and no lymph nodes affected. In 1 out of 19 (5.26%) patient clinically relapsed with a positive MRD detection 6 months earlier. Applying this methodology, we observed a sensitivity of 0.004% in ctDNA detection and 0.224 CTCs per mL of blood. Overall, this novel methodology greatly improves sensitivity for ctDNA and CTCs detection in treatment-naïve early BC. In addition, MRD was successfully detected in post-treatment samples antedating clinical relapse by 6 months in one patient. This prospective study is potentially demonstrating that using high blood volumes and a single-assay ddPCR is a cost-effective strategy to monitor localized BC and predict relapses. Citation Format: Alfonso Alba-Bernal, Ana Godoy-Ortiz, María Emilia Domínguez-Recio, Begoña Jimenez-Rodriguez, María Elena Quirós-Ortega, Esperanza López-López, Guillermo Carbajosa-Antona, Jesús Peralta-Linero, Luis Vicioso, Estefanía Bellagarza-García, Guadalupe Dolores Garrido-Ruiz, Cynthia Robles-Podadera, Alicia Garrido-Aranda, María Dunia Roldán-Díaz, Jesús Velasco-Suelto, Rocío Lavado-Valenzuela, Martina Álvarez, Nuria Ribelles, Javier Pascual, Emilio Alba, Iñaki Comino-Méndez. Increasing blood volumes to detect minimal residual disease in neoadjuvant-treated early breast cancer patients. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6610.

Introduction: While pCR has been amply associated with improved treatment outcome in patients treated with NAC and surgery, there are only few studies that explore the molecular determinants of pCR. Given the discrete percentage of patients who achieve pCR after NAC, it is of upmost need to identify biomarkers that can discern between responder and non-responder patients before NAC and therefore determine the best therapeutic approach in advance. Our aim is to find the best combination of variables to predict pCR in our cohort. Patients: To evaluate if there is a gene expression profile that could predict pathological complete response (pCR) to NAC, we selected a cohort of 69 patients treated with neoadjuvant chemotherapy consisting of anthracyclines + taxanes; HER2+ patients were further treated with trastuzumab. The median age was 48 years, and 71% of patients were premenopausal. The median of mammographic tumor size was 3,7. Most patients (89%) had invasive ductal carcinoma, and the histological grade was mainly 2 (55,7% Grade 1+2; 44,3% Grade 3). ER and PR positivity were seen in 63% and 53% of cases respectively. HER2 overexpression was seen in 20% of tumors. Methods: Gene expression was evaluated in 770 genes involved in 13 canonical cancer pathways as screened with the nCounter® PanCancer Pathways panel in FFPE pre-treatment tumor biopsies and analyzed with the nSolverTM software. The collected clinical and pathologic variables were age, mammographic tumor size, nodal status, tumor grade, HR status, HER2-overexpression, Ki67 percentage, IHQ subtype and PAM50 subtype. Finally, LASSO regression was used to predict pCR based on normalized gene expression levels and clinical and pathological data. Results: Out of the 69 enrolled patients, 27 achieved pCR (39%) and 42 did not (determined by Miller and Payne criteria). High-quality RNA was isolated from each patient for doing Nanostring nCounter experiment. Based on the gene expression levels of the PanCancer Pathways panel, Lasso regression identified a subset of genes as predictive of pCR. Therefore, the combination of expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 genes, predicted pCR with an average 70% of Area Under the Curve ROC (AUC) on the test set in a cross-validation scheme. DTX3 is a member of Notch pathway, IL11 from JAK-STAT pathway, CACNA1G from MAPK pathway, ETV4 and TSPAN7 from Transcriptional misregulation pathway. DTX3, CACNA1G and TSPAN7 are down-regulated and IL11 and ETV4 are up-regulated in patients who achieved pCR. Regarding the clinical and pathological data, the best model for predict pCR obtained an 60% of AUC and the selected variables were age, mammographic tumor size, nodal status, tumor grade and Ki67 percentage. Conclusions: In our cohort, the combination of gene expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 can predict tumor response to NAC even better than any clinical or pathological variable. Although validation in a separate cohort is necessary, our results indicate that this combination could constitute a predictive gene signature to discriminate resistant patients to NAC before the treatment in breast cancer tumors. Citation Format: Maria Rosario Chica-Parrado, Julio Montes-Torres, Cynthia Robles-Podadera, Martina Alvarez, Jose Jerez, Luis Vicioso, Lidia Pérez-Villa, Begoña Jimenez, Nuria Ribelles, Ana Godoy, Isabel Barragán-Mallofret, Emilio Alba. Gene expression levels of DTX3, CACNA1G, IL11, ETV4 and TSPAN7 selected by LASSO penalty regression could predict pCR after neoadjuvant chemotherapy in breast cancer tumors [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P1-10-26.

Melanoma comprises a variety of malignant cell types from the skin, the mucous membranes, and the pigmented cells of the eye. Its incidence and mortality rates continue to rise worldwide, mainly driven by increased ultraviolet light exposure. Although screening improvements have led to a better diagnosis in the early stages, the outcome for patients with Metastatic Melanoma (MM) remains poor and the survival rate is considerably low. Recently, Immune Checkpoint Inhibitors (ICB) have revolutionized the treatment of MM, although only 30% of patients enjoy clinical benefit and a plethora of different molecular mechanisms is postulated to cause resistance. Several biomarkers are currently on the spotlight as putative predictors of response; however, they are not sufficiently informative and robust. Circular RNAs (circRNAs) are a class of single-stranded stable RNAs produced by 5′-to-3′ transcription of coding gene exons or long non-coding RNAs that act as translation templates, RNA-binding protein regulators, or miRNA-binding sponges. Here, we present an exploratory study to evaluate the potential use of circRNA as ICB response predictors. We recruited 23 MM patients treated with Nivolumab and categorized them as good responders (10 patients) and bad responders (11 patients). All RNA-seq with ribosomal depletion was performed on RNA isolated from pre-treatment FFPE tumor biopsies. Two bioinformatic tools that use de novo assembly for the identification of circRNAs (Starchip and Ciri) were employed independently to characterize the MM circRNAs profile and to identify a specific pattern for responders. Overall, a total of 731 circRNAs were detected. Interestingly, the number of circRNAs were comparatively higher in bad responders (11.917 reads, 321 circRNAs) versus good responders (7368 reads, 176 circRNAs), with 234 common circRNAs. Additionally, we also explored the biological function of the identified circRNAs in MM, by interrogating KEGG, GO and Reactome databases to delineate the gene regulatory networks specifically associated with the response-related phenotypes. The circRNAs exclusively expressed in patients presenting resistance to Nivolumab were associated with Transcriptional Misregulation in Cancer and Viral Infections processes. In contrast, circRNAs expressed uniquely in good responders were enriched in Generic Transcription pathways. Importantly, amongst the identified circRNAs, CDR1-AS was differentially downregulated in good responders (536 vs 1580 reads, p-value 0.002). Remarkably, CDR1-AS acts as miRNA-binding sponge of miRNA-7 in the context of invasion and migration in melanoma. In conclusion, our exploratory study paves the way to the utilization of novel biomarkers associated to immunotherapy failure in MM patients. Moreover, our results suggest that CDR1-AS is a novel putative predictor of ICB response. Citation Format: Juan Luis Onieva, Javier Oliver, Aurora Laborda-Illanes, Maria Rosario Chica-Parrado, Alicia Garrido-Aranda, Cynthia Robles-Podadera, Daniel Prieto, Elena Gallego, Alfonso Sanchez, Iñaki Comino, Vanessa De Luque, Martina Alvarez, Maria Jose Lozano, Pedro Jimenez, Miguel Angel Berciano-Guerrero, Emilio Alba, Manuel Cobo, Isabel Barragan. Evaluation of circular RNA profiling in metastatic melanoma patients treated with immune checkpoint blockade [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 281.