Cancer Treatment Response Research Articles

Treatment of cancer-associated fibroblast-like cells with celecoxib enhances the anti-cancer T helper 1/Treg responses in breast cancer.

Tumor inflammation, as one of the hallmarks of cancer, has been the target for anti-cancer treatments. Celecoxib is a selective inhibitor of the enzyme cycloxygenase-2 (COX-2) and inhibits the production of PGE2, which is an important mediator of tumor inflammation produced by cancer cells and cells of the tumor microenvironment. In this study, we aimed at inhibiting COX-2 using celecoxib, expressed in cancer-associated fibroblast (CAF)-like cells isolated from breast cancer and evaluated the alterations in their cytokine profile and gene expression. CAF-like cells were isolated by explant culture from 13 breast cancer tissues. Simultaneously, peripheral blood mononuclear cells (PBMCs) were isolated from patients' blood. CAF-like cells were treated with 10µM of celecoxib and expression of genes COX-2, smooth muscle actin-alpha (α-SMA), and production of prostaglandin E2 (PGE2), Interleukin 10 (IL10), and transforming growth factor beta1 (TGF-β1) was evaluated. Next, PBMCs were co-cultured with celecoxib-treated CAF-like cells and the expression of genes T-bet, Foxp3, GATA-3; production of cytokines IFN-ɣ, IL-10, IL-4, TGF-β1, and the mediator PGE2 were assessed by real-time-PCR and ELISA, respectively. Isolated CAF-like cells showed expression of fibroblast activation protein (FAP). Treatment with celecoxib was able to efficiently reduce the production of PGE2 and the expression of α-SMA in isolated CAF-like cells. Furthermore, PBMCs in co-culture with these cells showed enhanced Th1 phenotype including T-bet and IFNγ expression and decreased the phenotypical markers of regulatory T cells such as FoxP3 and IL-10 and TGF-β1 production. Our study shows the important role of COX-2 in CAFs by promoting immune suppression. Our results suggested that high expression of COX-2 in CAFs may serve as a new therapeutic, targeting CAFs in enhancing immune responses in breast cancer treatment.

Inference of genetic ancestry from a multi-gene cancer panel in Colombian women with cancer.

Cancer health disparities among racial and ethnic populations significantly burden health systems due to unequal access to early detection, treatment, and healthcare resources. These disparities lead to worse outcomes and increased costs from delayed diagnoses, advanced treatments, and prolonged care. Genetic differences can also influence cancer susceptibility and treatment response, thus analyzing genetic ancestry is essential for uncovering genetic factors that may contribute to these disparities. Utilizing data from clinical multigene cancer panels to infer genetic ancestry offers a valuable approach to understand population structure and the impact of individual ancestries in development of complex diseases. To evaluate the accuracy of global ancestry inference using genetic markers from the TruSight™ Hereditary Cancer Panel, which was used to investigate hereditary cancer syndromes in a cohort of 116 female cancer patients at the Colombian National Cancer Institute. Additionally, to compare these results with genetic ancestry estimations from traditional genome-wide markers. Our results demonstrate a strong correlation between global genetic ancestry inferred with markers captured from TruSightTM panel (4785 markers) and Whole Genome Sequencing (WGS, 8 million markers in admixed populations. The correlation values were 0.96 (p < 0.0001) for the Native American and European ancestry components, and 0.99 (p < 0.0001) for the African ancestry fraction. Genetic ancestry mean proportions in the Colombian cohort were 45.7%, 46.2%, and 8.11% for the European, the Native American, and the African components, respectively. This study demonstrates the accuracy of ancestry inference from clinical panel data offering a promising approach for understanding cancer health disparities in admixed populations.

Characterization of tumor-infiltrating lymphocytes and their spatial distribution in triple-negative breast cancer

BackgroundThe tumor immune microenvironment, particularly tumor-infiltrating lymphocytes (TILs), plays a critical role in disease progression and treatment response in triple-negative breast cancers (TNBCs). This study was aimed to characterize the composition of TILs and investigate their clinicopathological and prognostic significance with a special focus on the spatial distribution of TILs in TNBCs.MethodsWe analyzed TNBC samples through PanCancer Immune Profiling using NanoString nCounter assays to identify immune-related genes that are expressed differentially in relation to TIL levels and evaluated protein expression of selected markers through immunohistochemical staining on tissue microarrays. For a comprehensive assessment of the expression of cytotoxic T lymphocyte (CTL) and natural killer (NK) cell markers, a CTL-NK score was devised based on CD8+, CD56+, CD57+, GNLY+, and GZMB+ TIL levels.ResultsGene expression analysis revealed significant upregulation of CTL and NK cell-associated genes including GNLY, KLRC2, and GZMB in TIL-high TNBCs. Immunohistochemical validation confirmed that TNBCs with higher TILs had a greater amount of CD56+, CD57+, GNLY+, and GZMB+ TILs not only in absolute number but also in proportion relative to CD4+ or CD8+ TILs. High TIL and its subset (CD4+, CD8+, CD56+, CD57+, GNLY+, and GZMB+ TIL) infiltration correlated with favorable clinicopathological features of tumor. In survival analysis, high CTL-NK score was found to be an independent prognostic factor for better disease-free survival (DFS) of the patients. Furthermore, uniformly high TIL infiltration was linked to better DFS, whereas cases with heterogeneous TIL infiltration showed no difference in survival compared to those with uniformly low TIL infiltration.ConclusionOur study showed that CTL and NK cell-associated gene expression and protein levels differ significantly according to TIL levels and that CTL-NK score and distribution of TILs within tumors have a prognostic value. These findings emphasize the importance of CTLs and NK cells as well as the spatial uniformity of TIL infiltration in clinical outcome of TNBC patients, providing valuable insights for refining prognostic assessments and guiding immunotherapeutic strategies.

Unveiling KLHL23 as a key immune regulator in hepatocellular carcinoma through integrated analysis.

Age-related cancers are characterized by impaired protein homeostasis, where Kelch protein superfamily members have showed accumulating clues as critical regulators. In this paper, the cancerous role of Kelch-like family member 23 (KLHL23) was comprehensively analyzed with TCGA and single cell GEO database across overall 33 cancer types. By multi-omics analysis upon the transcriptomic, genomic, and methylation data, the current study explored the association of KLHL23 with patient survival, gene ontology, tumor-infiltrating lymphocytes, and drug responses. The correlation of copy number variations and methylation with dysregulated expression of KLHL23 were also addressed. Notably, KLHL23 levels correlated with survival in cancers such as hepatocellular carcinoma and low-grade glioma. The study also highlighted how reduced KLHL23 expression is linked to increased immune activity and sensitivity to chemotherapy, suggesting its potential as a biomarker for cancer prognosis and treatment responsiveness.

Evaluating the Clinico-Pathological Relationship Between Stromal Tumor-Infiltrating Lymphocytes and Androgen Receptor Expression Across Molecular Subtypes of Invasive Breast Carcinoma.

Breast cancer remains a significant cause of mortality globally, necessitating effective treatment strategies. Neoadjuvant chemotherapy (NAC) is widely employed to minimize tumor burden and prevent local spread, with treatment efficacy varying based on molecular subtypes. Despite advancements, resistance to conventional therapies persists, prompting the exploration of alternative approaches, including immune cell therapy. Tumor-infiltrating lymphocytes (TILs) have emerged as immunological biomarkers in breast cancer, exhibiting associations with molecular subtypes and treatment response. This retrospective study assessed the clinico-pathological relationship between stromal TILs and AR expression across molecular subtypes of invasive breast carcinoma in an Indian cohort. Thirty-seven patients receiving NAC followed by modified radical mastectomy were analyzed for TILs and molecular subtyping. Immunohistochemistry was used to determine hormone receptor status and AR expression. A higher AR positivity was observed in hormone receptor-positive/Her2neu-negative and hormone receptor-positive/Her2neu-positive tumors compared to triple-negative breast cancers (TNBCs). Significant associations were observed between AR expression and tumor grade, but not with age or Her2neu status. Although no significant correlation was found between AR and complete response to NAC, a weak negative correlation between AR and TILs was noted. Notably, TNBCs with negative AR and Ki67 index exhibited poorer responses to NAC, emphasizing the need for adjuvant therapy. These findings underscore the complex interplay between AR, TILs, and treatment response in breast cancer, highlighting the potential of personalized therapeutic approaches. Further research is warranted to elucidate the prognostic significance of AR and its implications for tailored treatment strategies in breast cancer management.

Assessing Large Language Models for Oncology Data Inference From Radiology Reports.

We examined the effectiveness of proprietary and open large language models (LLMs) in detecting disease presence, location, and treatment response in pancreatic cancer from radiology reports. We analyzed 203 deidentified radiology reports, manually annotated for disease status, location, and indeterminate nodules needing follow-up. Using generative pre-trained transformer (GPT)-4, GPT-3.5-turbo, and open models such as Gemma-7B and Llama3-8B, we employed strategies such as ablation and prompt engineering to boost accuracy. Discrepancies between human and model interpretations were reviewed by a secondary oncologist. Among 164 patients with pancreatic tumor, GPT-4 showed the highest accuracy in inferring disease status, achieving a 75.5% correctness (F1-micro). Open models Mistral-7B and Llama3-8B performed comparably, with accuracies of 68.6% and 61.4%, respectively. Mistral-7B excelled in deriving correct inferences from objective findings directly. Most tested models demonstrated proficiency in identifying disease containing anatomic locations from a list of choices, with GPT-4 and Llama3-8B showing near-parity in precision and recall for disease site identification. However, open models struggled with differentiating benign from malignant postsurgical changes, affecting their precision in identifying findings indeterminate for cancer. A secondary review occasionally favored GPT-3.5's interpretations, indicating the variability in human judgment. LLMs, especially GPT-4, are proficient in deriving oncologic insights from radiology reports. Their performance is enhanced by effective summarization strategies, demonstrating their potential in clinical support and health care analytics. This study also underscores the possibility of zero-shot open model utility in environments where proprietary models are restricted. Finally, by providing a set of annotated radiology reports, this paper presents a valuable data set for further LLM research in oncology.

High-resolution crystal structure of PD-1 in complex with retifanlimab, the FDA-approved immune checkpoint blocking antibody for treating Merkel cell carcinoma

Retifanlimab is a humanized monoclonal antibody that specifically targets programmed cell death protein 1 (PD-1), an essential immune checkpoint that modulates T-cell immune responses. Several anti-PD-1 antibodies have been market-approved, marking a significant advancement in the treatment of diverse tumor types by restoring the T-cell immune response. Recently, the US FDA approved retifanlimab for treating metastatic or recurrent locally advanced Merkel cell carcinoma. We present the crystal structure of PD-1 in complex with the retifanlimab Fab at a resolution of 1.54 Å to elucidate the structural basis for the mechanism of action of this antibody. This work clarifies the detailed interactions and conformational alterations that occur upon antibody binding. The epitope of retifanlimab partially overlaps with the ligand binding site, and its binding induced unique conformations of the flexible loops within PD-1, including BC, C'D, and FG loops, thereby optimizing interactions with the antibody. A thorough analysis of its interaction with PD-1 and other FDA-approved anti-PD-1 antibodies may provide valuable insights into the rational design of enhanced therapies to regulate immune responses in cancer treatment.

A novel necroptosis-related genes signature to predict prognosis and treatment response in bladder cancer.

Necroptosis, a form of programmed inflammatory cell death, plays a crucial role in tumor development, necrosis, metastasis, and immune response. This study aimed to explore the role of necroptosis in BLCA and construct a new prognostic model to guide clinical treatment and predict individualized treatment response. The transcriptome profiling and the corresponding clinical data of BLCA patients were obtained from the Cancer Genome Atlas database (TCGA) and GEO databases. Univariate, multivariate and LASSO Cox regression analyses were used to identify and construct prognostic features associated with necroptosis. We constructed and validated a prognostic model associated with the patient's overall survival (OS). A nomogram was established to predict the survival rates of BLCA patients. Finally, the correlation between risk scores and tumor immune microenvironment, somatic mutations, immunotherapy, and chemotherapy was comprehensively analyzed. The study found two distinct NRG clusters and three gene subtypes, with significant differences in pathway enrichment and immune cell infiltration associated with different NRG clusters in the TME. In addition, we screened out six necroptosis prognosis-related genes (including PPP2R3A; CERCAM; PIK3IP1; CNTN1; CES1 and CD96) to construct a risk score prognostic model. Significant differences in overall survival rate, immune cell infiltration status, and somatic mutations existed between the high and low-risk scores in BLCA patients. Finally, drug sensitivity analysis showed that high-risk patients benefited more from immunotherapy and chemotherapy drugs. This study explores the importance of necroptosis in the prognosis of patients with BLCA, and the prognostic features associated with necroptosis that we identified can serve as new biomarkers to help develop more precise treatment strategies.

Quantitative MRI Measurements Capture Pancreatic Cancer and Stroma Reactions to New KRAS Inhibitor.

Emerging small molecule KRAS inhibitors (KRASi) represent a new class of therapy for PDAC. Clinical tools that can provide biological insights beyond tumor size change are desirable for management of patients under KRASi therapy. DWI and DCE are frequently applied MRI methods for assessing cancer treatment responses in clinical trials. Using multiple PDAC models, we examined whether DWI, DCE and MTR can enhance the standard care assessment (tumor size) to MRTX1133, a KARSi with investigational new drug (IND) status. Our data demonstrate the abilities of DWI, DCE and MTR derived imaging markers to detect the early (48h) cell death, pronounced stromal changes and development of resistance to KRASi. This study has high translational relevance by testing clinically ready MRI methods, an IND and a genetic engineered mouse model that recapitulates saline features of human PDAC.

DEPTH2 score was associated with cell proliferation and immune cell infiltrations but not with systemic treatment response in breast cancer.

Intratumoral genomic heterogeneity (ITGH), the existence of genotypic and phenotypic variation within an individual tumor, is known to be a key mechanism in treatment resistance. Deviating gene Expression Profiling Tumor Heterogeneity 2 (DEPTH2) algorithm was developed to estimate ITGH using solely RNA expression data unlike the others that require both DNA- and RNA-expression data. Total of 6,500 breast cancer patients from multiple independent cohorts were analyzed using DEPTH2. High DEPTH2 score patients were associated with worse overall survival consistently across all subtypes in METABRIC, but not in TCGA and SCAN-B cohort. Higher DEPTH2 score was linked to increased cell proliferation, as evidenced by elevated Nottingham histological grades and Ki67 gene expression, as well as enrichment of the cell proliferation-related gene sets, and immune cell infiltrations. DEPTH2 score was significantly higher in triple negative breast cancer among the subtypes but did not reflect with lymph node and distal metastasis. DEPTH2 scores decreased in two but showed no change in another two cohorts after neoadjuvant chemotherapy (NAC). DEPTH2 score was not associated with pathologic complete response after NAC in any subtypes across 3 cohorts. DEPTH2 score may not capture the entire biological aspects of ITGH in breast cancer patients.

Abstract A018: Endothelial pyrimidine synthesis deficiency promotes tumor growth

Abstract The tumor microenvironment plays a crucial role in cancer progression and treatment response. Systemically administered metabolic cancer therapies target not only malignant but also stromal cells, including immune cells - the only stromal population previously addressed in this context. However, how such treatments impact other non-malignant cell types in tumors remains poorly understood. Here we show that inhibition of de novo pyrimidine synthesis in endothelial cells accelerates tumor growth and alters tumor immune repertoire. We found that whole-body de novo pyrimidine synthesis deficiency in mice, caused by the inducible whole-body ablation of DHODH, accelerates the growth rate of orthotopic lung tumors. Single-cell transcriptomic analysis of tumor-bearing lungs revealed that DHODH deficiency in the stroma impacts multiple cell populations, including immune and, surprisingly, endothelial cells. To explore the endothelial-specific effects, we generated a mouse model with inducible DHODH deficiency restricted to endothelial cells. The endothelium-specific model recapitulates the accelerated lung tumor growth observed in the whole-body DHODH deficiency model. Single-cell transcriptomics analysis of tumor-bearing lungs in the endothelium-specific model pointed to changes in the immune repertoire, particularly an enrichment of monocytes. We confirmed these results on the protein level using spectral flow cytometry, and we are currently in the process of uncovering the mechanism by which endothelial deficiency of pyrimidine synthesis affects the immune landscape of tumors. Inhibitors of pyrimidine de novo synthesis have been tested in clinical trials but failed due to their low efficiency. Our findings indicate that systemic treatment targeting pyrimidine synthesis may be hampered by its pro-tumorigenic effects in the endothelium, highlighting the unexpected role of endothelial metabolism in this context. Citation Format: Petra Hyrossova, Isidora Milisav, Silvia Novais, Mirko Milosevic, Jakub Rohlena, Katerina Rohlenova. Endothelial pyrimidine synthesis deficiency promotes tumor growth [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A018.

Abstract B013: An mDETECT assay for monitoring treatment response in metastatic breast cancer patients

Abstract Metastatic breast cancer treatment response is currently assessed every 3-6 months and this long delay results in many patients undergoing ineffective and toxic treatments for long periods of time. We have developed the methylation DETEction of Circulating Tumour DNA (mDETECT) assay, a targeted DNA methylation-based Next Generation Sequencing liquid biopsy that detects cancer-specific patterns in all subtypes of breast cancer. The assay targets 60 differentially hypermethylated regions in breast cancer across the genome and assesses over 400 individual CpGs with an average of 8 CpGs per target amplicon. The assay has been assessed on DNA from 73 breast cancer tumour samples which on average had 40 regions hypermethylated per patient with similar rates across all subtypes. We will present results from plasma samples from locally advanced and metastatic breast cancer patients along with plasma from age-matched, healthy female controls. A prospective, multi-centre observational cohort study to monitor metastatic breast cancer patients using the mDETECT liquid biopsy as they undergo treatment is active and recruiting patients. Blood is drawn with every standard-of-care blood draw for up to 3 years. Plasma has been assessed using the mDETECT assay to determine the methylation status of the DNA at each time point. 35 patients have been enrolled to date with ongoing recruitment up to 150 patients. Patients are being monitored with the mDETECT assay for earlier detection of disease progression on a treatment. They will also be monitored through treatment changes to assess a patient’s initial response to a given treatment. Changes in mDETECT levels will be correlated with clinical response to determine if the mDETECT breast cancer assay can detect a response to treatment at an earlier timepoint. This assay could allow for improved monitoring of treatment response allowing clinicians to make informed decisions, improving outcomes and prolonging patient’s lives. Citation Format: Keira Frosst, Brooke Wilson, Katrina Cristall, Catherine Crawford-Brown, Christopher R Mueller. An mDETECT assay for monitoring treatment response in metastatic breast cancer patients [abstract]. In: Proceedings of the AACR Special Conference: Liquid Biopsy: From Discovery to Clinical Implementation; 2024 Nov 13-16; San Diego, CA. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(21_Suppl):Abstract nr B013.

Automated Quantification of Tertiary Lymphoid Structures in Human Tumor Samples Using Immunofluorescence and AI-Powered Analysis Pipeline.

The tumor microenvironment (TME) is a complex entity comprising not only tumor cells but also immune, stromal, and endothelial cells. Preclinical and clinical studies indicate that the density, localization, function, and organization of immune infiltration can influence survival probability and treatment response in many cancers. Among these cell organizations, the clustering of T and B cells into tertiary lymphoid structures (TLS) has been associated with favorable clinical outcomes. In this protocol, we propose a protocol for 7-plex immunofluorescence staining for identifying six cell types enriched in TLS in formalin-fixed paraffin-embedded (FFPE) human tumor sections. Additionally, we provide a detailed methodology for quantifying these cell subtypes using the Halo-AI analysis software. This approach will enable a more precise and detailed characterization of TLS in the TME, opening new avenues for understanding their role in anticancer treatment response.

Integration of Machine Learning and Experimental Validation to Identify Anoikis-Related Prognostic Signature for Predicting the Breast Cancer Tumor Microenvironment and Treatment Response.

Background/Objectives: Anoikis-related genes (ANRGs) are crucial in the invasion and metastasis of breast cancer (BC). The underlying role of ANRGs in the prognosis of breast cancer patients warrants further study. Methods: The anoikis-related prognostic signature (ANRS) was generated using a variety of machine learning methods, and the correlation between the ANRS and the tumor microenvironment (TME), drug sensitivity, and immunotherapy was investigated. Moreover, single-cell analysis and spatial transcriptome studies were conducted to investigate the expression of prognostic ANRGs across various cell types. Finally, the expression of ANRGs was verified by RT-PCR and Western blot analysis (WB), and the expression level of PLK1 in the blood was measured by the enzyme-linked immunosorbent assay (ELISA). Results: The ANRS, consisting of five ANRGs, was established. BC patients within the high-ANRS group exhibited poorer prognoses, characterized by elevated levels of immune suppression and stromal scores. The low-ANRS group had a better response to chemotherapy and immunotherapy. Single-cell analysis and spatial transcriptomics revealed variations in ANRGs across cells. The results of RT-PCR and WB were consistent with the differential expression analyses from databases. NU.1025 and imatinib were identified as potential inhibitors for SPIB and PLK1, respectively. Additionally, findings from ELISA demonstrated increased expression levels of PLK1 in the blood of BC patients. Conclusions: The ANRS can act as an independent prognostic indicator for BC patients, providing significant guidance for the implementation of chemotherapy and immunotherapy in these patients. Additionally, PLK1 has emerged as a potential blood-based diagnostic marker for breast cancer patients.

Association Between Phosphorylated AXL Expression and Survival in Patients with Gastric Cancer.

Background: Gastric cancer (GC) is a leading cause of cancer-related mortality, particularly in East Asia. Despite treatment advances, the prognosis remains poor owing to late diagnosis and high metastatic potential. Phosphorylated AXL (pAXL), a receptor tyrosine kinase, promotes cancer progression, including epithelial-mesenchymal transition (EMT), tumor growth, and metastasis. In this study, we aimed to investigate the relationship between pAXL expression and prognosis in patients with GC, focusing on survival outcomes and other biomarkers such as fibronectin and phosphorylated AKT (pAkt). Methods: Immunohistochemistry was performed to assess the expression of pAXL, fibronectin, and pAkt in 188 GC specimens collected between 2000 and 2013. H-scores were calculated based on staining intensity and percentage. The association between pAXL expression and patient outcomes was assessed using Kaplan-Meier survival analysis and multivariate logistic regression. Results: Higher pAXL expression was significantly associated with improved survival, particularly in male patients. pAXL expression positively correlated with fibronectin and pAkt upregulation, suggesting its role in promoting tumor invasion and EMT. Multivariate analysis identified pAXL, fibronectin, and pAkt as significant prognostic indicators, whereas other factors such as age, tumor grade, and tumor size were not statistically significant. Conclusions: This study identified pAXL as a valuable prognostic marker in GC, with higher expression levels associated with better survival outcomes, particularly in male patients. pAXL enhanced the invasive potential of GC cells through fibronectin and pAkt regulation, making it a promising therapeutic target. Further research is needed to explore the potential of pAXL-targeted therapies and better understand their role in cancer progression and treatment response.

Culturally responsive strategies and practical considerations for live tissue studies in Māori participant cohorts.

Indigenous communities globally are inequitably affected by non-communicable diseases such as cancer and coronary artery disease. Increased focus on personalized medicine approaches for the treatment of these diseases offers opportunities to improve the health of Indigenous people. Conversely, poorly implemented approaches pose increased risk of further exacerbating current inequities in health outcomes for Indigenous peoples. The advancement of modern biology techniques, such as three-dimensional (3D) in vitro models and next generation sequencing (NGS) technologies, have enhanced our understanding of disease mechanisms and individualized treatment responses. However, current representation of Indigenous peoples in these datasets is lacking. It is crucial that there is appropriate and ethical representation of Indigenous peoples in generated datasets to ensure these technologies can be used to maximize the benefit of personalized medicine for Indigenous peoples. This project discusses the use of 3D tumor organoids and single cell/nucleus RNA sequencing to study cancer treatment responses and explore immune cell roles in coronary artery disease. Using key pillars from currently available Indigenous bioethics frameworks, strategies were developed for the use of Māori participant samples for live tissue and sequencing studies. These were based on extensive collaborations with local Māori community, scientific leaders, clinical experts, and international collaborators from the Broad Institute of MIT and Harvard. Issues surrounding the use of live tissue, genomic data, sending samples overseas and Indigenous data sovereignty were discussed. This paper illustrates a real-world example of how collaboration with community and the incorporation of Indigenous worldviews can be applied to molecular biology studies in a practical and culturally responsive manner, ensuring fair and equitable representation of Indigenous peoples in modern scientific data.

CTR-DB 2.0: an updated cancer clinical transcriptome resource, expanding primary drug resistance and newly adding acquired resistance datasets and enhancing the discovery and validation of predictive biomarkers.

Drug resistance is a principal limiting factor in cancer treatment. CTR-DB, the Cancer Treatment Response gene signature DataBase, is the first data resource for clinical transcriptomes with cancer treatment response, and meanwhile supports various data analysis functions, providing insights into the molecular determinants of drug resistance. Here we proposed an upgraded version, CTR-DB 2.0 (http://ctrdb.ncpsb.org.cn). Around 190 up-to-date source datasets with primary resistance information (129% increase compared to version 1.0) and 13 acquired-resistant datasets (a new dataset type), covering 10 856 patient samples (111% increase), 39 cancer types (39% increase) and 346 therapeutic regimens (26% increase), have been collected. In terms of function, for the single dataset analysis and multiple-dataset comparison modules, CTR-DB 2.0 added new gene set enrichment, tumor microenvironment (TME) and signature connectivity analysis functions to help elucidate drug resistance mechanisms and their homogeneity/heterogeneity and discover candidate combinational therapies. Furthermore, biomarker-related functions were greatly extended. CTR-DB 2.0 newly supported the validation of cell types in the TME as predictive biomarkers of treatment response, especially the validation of a combinational biomarker panel and even the direct discovery of the optimal biomarker panel using user-customized CTR-DB patient samples. In addition, the analysis of users' own datasets, application programming interface and data crowdfunding were also added.

P214 Circulating tumor DNA (ctDNA) in surveillance and monitoring of treatment response in testis cancer- A retrospective institutional review

P214 Circulating tumor DNA (ctDNA) in surveillance and monitoring of treatment response in testis cancer- A retrospective institutional review

Magnitude of antigen-specific T-cell immunity the month after completing vaccination series predicts the development of long-term persistence of antitumor immune response

BackgroundFor best efficacy, vaccines must provide long-lasting immunity. To measure longevity, memory from B and T cells are surrogate endpoints for vaccine efficacy. When antibodies are insufficient for protection, the...

The Role of the Microbiome and of Radiotherapy-Derived Metabolites in Breast Cancer.

The gut microbiome has emerged as a crucial player in modulating cancer therapies, including radiotherapy. In the case of breast cancer, the interplay between the microbiome and radiotherapy-derived metabolites may enhance therapeutic outcomes and minimize adverse effects. In this review, we explore the bidirectional relationship between the gut microbiome and breast cancer. We explain how gut microbiome composition influences cancer progression and treatment response, and how breast cancer and its treatments influence microbiome composition. A dual role for radiotherapy-derived metabolites is explored in this article, highlighting both their therapeutic benefits and potential hazards. By integrating genomics, metabolomics, and bioinformatics tools, we present a comprehensive overview of these interactions. The study provides real-world insight through case studies and clinical trials, while therapeutic innovations such as probiotics, and dietary interventions are examined for their potential to modulate the microbiome and enhance treatment effectiveness. Moreover, ethical considerations and patient perspectives are discussed, ensuring a comprehensive understanding of the subject. Towards revolutionizing treatment strategies and improving patient outcomes, the review concludes with future research directions. It also envisions integrating microbiome and metabolite research into personalized breast cancer therapy.