Circulating tumor cells (CTCs) are a group of cells that travel through the circulatory system of a cancer patient, sowing distant sites and forming the seeds for metastatic nodules. Studying the genetic mechanisms involved in the CTC phenotype could enable significant strides in understanding metastasis. Initially, CTC studies were limited in scope to the enumeration of this rare population of cells. However, recent advancements in expanding viable CTCs ex vivo made in the last two decades have enabled researchers to properly interrogate this new frontier of metastatic research, resulting in groundbreaking findings expanding upon the simplistic models of metastasis previously used. In this chapter, we will focus on the technological advancements that have enabled the isolation and propagation of CTCs. First, we will highlight two eras of CTC culture: one focused on growing viable epithelial cells and the other focused on modeling CTC heterogeneity, such as through the capture of CTC clusters. Next, we will explore methods for generating in vivo CTC-derived xenograft (CDX) models. We will further compare and contrast these methods, discussing where these models fit within the spectrum of metastasis models. Finally, we will preview how CTC expansion may play a crucial role in the era of personalized medicine.

Circulating tumor cells (CTCs) provide a minimally invasive window into metastatic disease but are constrained by the need for rapid specimen processing after blood collection. We evaluated whether a workflow utilizing BD Vacutainer CPT-based blood collection could support delayed processing while preserving molecular features of propagated CTC-derived material. In a pilot cohort of four patients, paired CPT tubes were collected; one tube was processed within 2 hours of phlebotomy, whereas the second was stored at 4°C and processed 24 hours later. Both tubes were then harvested for CTCs, which were propagated ex vivo and analyzed by bulk RNA sequencing and whole-exome sequencing. Transcriptomic analyses showed that paired CPT-derived samples demonstrated phenotypes consistent with CTCs, including reduced immune-associated signatures and enrichment of epithelial-mesenchymal transition and KRAS signaling pathways. Direct comparison of paired early- and delayed-processed CPT samples demonstrated strong within-patient gene expression concordance. Whole-exome sequencing further revealed preservation of patient-specific oncogenic alterations and high overlap of detected variants across paired processing conditions. These findings altogether support the feasibility of a CPT-based delayed processing workflow for propagating and studying CTCs, thereby reducing a key logistical barrier to broader CTC research.

In the original publication [...].

Background/Objectives: Pancreatic adenocarcinoma (PDAC) remains one of the most lethal cancers, with limited advancements in treatment efficacy due to high rates of chemoresistance. Circulating tumor cells (CTCs) derived from liquid biopsies offer a non-invasive approach to monitoring tumor evolution and identifying molecular mechanisms of resistance. This study aims to longitudinally collect, culture, and characterize CTCs from PDAC patients to elucidate resistance mechanisms and tumor-specific gene expression profiles. Methods: Blood samples from 10 PDAC patients were collected across different treatment stages, yielding 16 CTC cultures. Differential gene expression, pathway dysregulation, and protein–protein interaction studies were utilized, highlighting patient-specific and disease progression-associated changes. Longitudinal comparisons within five patients provided further insights into dynamic molecular changes associated with therapeutic resistance. Results: CTC cultures exhibited the activation of key pathways implicated in PDAC progression and resistance, including TNFα/NF-kB, hedgehog signaling, and the epithelial-to-mesenchymal transition. Longitudinal samples revealed dynamic changes in signaling pathways, highlighting upregulated mechanisms of chemoresistance, including PI3K/Akt/mTOR and TGF-β pathways. Additionally, protein–protein interaction analysis emphasized the role of the immune system in PDAC progression and therapy response. Patient-specific gene expression patterns therefore suggest potential applications for precision medicine. Conclusions: This proof-of-concept study demonstrates the feasibility of longitudinally capturing and analyzing CTCs from PDAC patients. The findings provide critical insights into molecular drivers of chemoresistance and highlight the potential of CTC profiling to inform personalized therapeutic strategies. Future large-scale studies are warranted to validate these findings and further explore CTC-based approaches in PDAC management.

560 Background: Incorporating molecular profiling in BTC treatment has increased. With this study, we aimed to analyze the impact of molecular profiles on the survival of patients with BTC. Methods: This is the retrospective analysis of patients with biopsy-proven biliary tract cancer at our comprehensive cancer center GI oncology clinic from 2018-2022. Only patients with continued care at Lombardi Comprehensive Cancer Center were included in the study. Results: Of 217 patients screened; 160 patients were included in the final analysis. The mean age of the cohort was 63 years, and the majority were females (55%). In the order of frequency, intrahepatic cholangiocarcinoma (77.5%) was the most common type of cancer followed by extrahepatic cholangiocarcinoma (15.6%), and carcinoma of the Gallbladder (6.9%). Molecular profiling was performed in 49.4% of the patients and actionable mutations for FDA approved treatments or clinical trial enrollment were found in 42 patients (26.3%) of the patients. The spectrum of actionable mutations in decreasing order of frequency was KRAS (n=11), FGFR2 (n=9), IDH-1 (n=8), Her-2neu (n=5), BRCA1/2 (n=5), & PD-L1(n=4). Patients who underwent molecular profiling had significantly better survival (43±5 months vs. 25±4, p 0.013). Notably, patients with actionable mutations had even better survival as compared to the rest of the cohort (52±8 months vs. 26±7 months, p 0.019). Conclusions: BTC exhibits diverse genetic alterations. Patients who underwent molecular profiling as a part of the treatment plan had better survival. Identifying actionable mutations was associated with even better survival.

Cancer is one of the world's most critical health issues. Many in the past decade More accurately, diagnostic tests and methodologies have been enhanced. Tests are categorised into imaging tests, endoscopic procedures Includes testing for biopsy and cytology. These diagnostic tests yield huge numbers. volumes of data that must be evaluated and differentiated by specialists Between tumours that are benign and malignant. Artificial intelligence now (AI) Large quantities of diagnostic imaging may be examined using applications Improved accuracy to enhance health system efficiency. New AI algorithms technical advances and computer enhancements Hardware may be used to train diagnostic neural artificial networks Experience with a wide range of scans. Already a thorough understanding and Machines can educate computers to compare and assess models Huge quantity of cancer scanning data. Highly diagnostic skills Software has been evaluated and compared to the conventional Cancer specialists' diagnostic tools. Their precision is much increased and regarded highly effective in early diagnosis and extended forecasting Different cancers. Scientists have become systems of artificial intelligence (AI). that may exceed human specialists in the prognosis of breast cancer and A great deal earlier diagnosis. Similarly, informatics developed an AI algorithm. and profound learning algorithms that may forecast to which persons Develop lung cancer using low dose CT analysis (computerized tomography) Lung scans. Lung scans. Use of the convolutionary neural network recently (CNNs) was employed in the invasion depth diagnosis of Gastric endoscopy-based gastric cancer. Studies have also been shown AI techniques paired with imagery may have a significant influence early diagnosis with algorithm-guided identification of oral cancer results Heterogeneity of the oral lesion. This review gathered some pretty interesting information Research publications on the topic.

805 Background: Studying CTC cultures (cx) ex-vivo can provide valuable insights into cancer metastases (mets). However, current immunoaffinity- and size-based-methods used to isolate and expand these cells have low success rates for culturing CTCs (6-20%). Here, we report our experience using a novel technology developed at Georgetown for culturing CTCs from patients (pts) with metastatic (m) CC, mPC, and locally advanced PC (LAPC). Methods: 44 peripheral blood samples were prospectively collected from 35 pts with adenocarcinoma across 3 cohorts (18 samples from 15 mCC pts, 21 samples from 15 mPC pts, and 5 samples from 5 LAPC pts). Pts were previously treated, treatment-naïve, or actively undergoing treatment. FiColl-Paque-based separation of red blood cells was performed, plasma and buffy coat cells were resuspended in cx medium, and successfully grown CTC cxs were processed and injected subcutaneously (subQ) in the flanks of mice. A single predetermined sample from each pt was used in assessing the clinicopathologic associations with experiment outcomes and survival analyses. Results: CTC cxs were successfully grown from 81.8% (36/44) of all samples. Cxs grew from 72.2% (13/18) of mCC, 85.7% (18/21) of mPC, and 100% (5/5) of LAPC samples. At the time of analysis, 25 injected mice were evaluable for subQ tumor growth. 4 mice failed to grow tumor, 10 were still under monitoring, and 11 grew tumor, 9 of which also developed mets. These were mostly macro-mets and partially mirrored the met pattern seen in the matched pt. Across all cohorts, samples were predominantly collected from pts during systemic treatment (79.5%), during 2nd- (36.4%) and 1st-line treatment (20.5%), at a median of 15 (0-111) and 5 (1-20) months after diagnosis in mPC/mCC and LAPC pts, respectively, after scans with new/progressing disease (72.7%), and with a median of 3 (1-9) sites of disease on scans done within 2 months of collection . In all pts, no clinicopathologic or genomic factor predicted for cx growth. In the mCC subgroup, female sex (p=0.044), longer time from diagnosis to CTC collection (p=0.033), and presence of lung mets (p=0.022) were associated with cx growth. With cohorts combined, the median pt progression-free survival was 174 days (95% CI 97-220) and median overall survival was not reached. There was no statistically significant relationship between cx growth and pt survival. Conclusions: This novel platform demonstrated historically high rates of successful CTC cx and xenograft tumor growth using samples from advanced CC and PC pts. Studies to elucidate reasons for mice failing to grow tumor and others with matched tumor-CTC molecular analyses are ongoing to validate this promising technology to ultimately use to identify biomarkers for metastases, uncover novel therapeutic targets, and inform clinical decisions.

Supplementary Materials and Methods and Supplementary Figure Legends

4087 Background: Over 20% of biliary tract cancers (BTCs) carry mutations in homologous recombination DNA damage repair (HR-DDR) pathways. The PARP inhibitor olaparib (O) blocks tumor DNA repair and may induce response in BTCs with such mutations. Furthermore, HR-DDR mutations may engender neoantigens that improve response to immune checkpoint inhibitors. We propose that treatment with O and the anti-PD-1 monoclonal antibody pembrolizumab (P) will produce a durable anti-tumor response to BTC, especially in patients with HR-DDR mutations. Methods: Consent for participation was obtained. Eligibility criteria included age > 18 years with an ECOG score of ≤1 and a histologic diagnosis of advanced or metastatic BTC with progression of disease (PD) on prior first-line therapy. Treatment featured oral O (300 mg twice daily) plus intravenous P (200 mg every 3 weeks). Response was measured radiographically using RECIST 1.1 guidelines. The primary endpoint was overall response rate (ORR), with the alternative hypothesis that O + P would improve ORR compared to historical controls (versus the null hypothesis of no improvement). Type I and II error rates were set at 5% and 15%, respectively. Simon’s optimal two-stage design was used. Planned sample size was 13 patients in the first stage. Continuation to the second stage would only occur if ≥3 patients demonstrated response. The second stage was planned to include 20 additional patients (N = 33 total), which was based on the number needed to demonstrate an improvement in ORR from 17.5% in historical controls to at least 35.0%. Results: Of 21 eligible patients, 14 were accrued between June 2020 and March 2022, and 13 were evaluable for efficacy. Patients had a median age of 63 years, were primarily female (71%), Caucasian (50%), and with metastatic disease (93%). Patients received a mean of 6.5 cycles of therapy. Best treatment response included partial response (N = 2), stable disease (N = 5), and PD (N = 6). The ORR was 15.3% (95% CI = 0.02-0.45). Of the partial responders, 1 patient achieved a duration of response of 8 months (mos), and 1 has ongoing response at 24 mos. Median (med) time to progression was 7.7 mos (95% CI = 1.2-9.3), med progression free survival was 5.5 mos (95% CI = 1.2-7.7), and med overall survival was 11.9 mos (95% CI = 5.5-15.4). Most patients (64%) developed at least one treatment-related adverse event (trAE). Grade 3 trAEs were experienced in 5 patients (36%) and included anemia (N = 3), diarrhea (N = 1), and transaminitis (N = 1). Conclusions: While O + P has acceptable safety and toxicity, the study did not achieve significant improvement in the primary endpoint. However, the two patients who demonstrated durable treatment response were found to have HR-DDR tumor mutations (including RAD51, ATM, and BRCA2), necessitating further research into the efficacy of O + P for patients with similar tumor genomes. Clinical trial information: NCT04306367 .

Breast cancer is the most frequent type of cancer in women; however, early identification has reduced the mortality rate associated with the condition. Studies have demonstrated that the earlier this sickness is detected by mammography, the lower the death rate. Breast mammography is a critical technique in the early identification of breast cancer since it can detect abnormalities in the breast months or years before a patient is aware of the presence of such abnormalities. Mammography is a type of breast scanning used in medical imaging that involves using x-rays to image the breasts. It is a method that produces high-resolution digital pictures of the breasts known as mammography. Immediately following the capture of digital images and transmission of those images to a piece of high-tech digital mammography equipment, our radiologists evaluate the photos to establish the specific position and degree of the sickness in the breast. When compared to the many classifiers typically used in the literature, the suggested Multiclass Support Vector Machine (MSVM) approach produces promising results, according to the authors. This method may pave the way for developing more advanced statistical characteristics based on most cancer prognostic models shortly. It is demonstrated in this paper that the suggested 2C algorithm with MSVM outperforms a decision tree model in terms of accuracy, which follows prior findings. According to our findings, new screening mammography technologies can increase the accuracy and accessibility of screening mammography around the world.

Circulating tumor cells (CTCs) are a group of cells that travel through the circulatory system of a cancer patient, sowing distant sites and forming the seeds for metastatic nodules. Given the unique role of CTCs, the study of this cell population could enable significant strides in understanding metastasis. The clinical importance of CTCs for predicting overall survival has been routinely demonstrated. Recently, advancements in culturing and expanding viable CTCs ex vivo made in the last two decades have further enabled researchers to properly interrogate this new frontier of metastatic research. Expansion of CTCs through in vitro cultures and in vivo CTC-derived xenograft models (CDXs) has resulted in groundbreaking findings significantly improving the rather simplistic models of metastasis previously used. In this chapter, we will focus on advancements made toward isolating and culturing CTCs both in a tissue culture plate and through the formation of CDX models. We will highlight two eras of CTC culture: one focused on growing viable epithelial cells and the other focused on modeling CTC heterogeneity. Next, we will explore methods for generating in vivo CTC-derived xenograft models. Comparing CDX models against CTC culture platforms, we will highlight the advantages and disadvantages of each method and where these models fit within the spectrum of metastasis models. Finally, we will preview how CTC expansion may play a crucial role in the era of personalized medicine.

Circulating tumor cells (CTCs), a population of cancer cells that represent the seeds of metastatic nodules, are a promising model system for studying metastasis. However, the expansion of patient-derived CTCs ex vivo is challenging and dependent on the collection of high numbers of CTCs, which are ultra-rare. Here we report the development of a combined CTC and cultured CTC-derived xenograft (CDX) platform for expanding and studying patient-derived CTCs from metastatic colon, lung, and pancreatic cancers. The propagated CTCs yielded a highly aggressive population of cells that could be used to routinely and robustly establish primary tumors and metastatic lesions in CDXs. Differential gene analysis of the resultant CTC models emphasized a role for NF-κB, EMT, and TGFβ signaling as pan-cancer signaling pathways involved in metastasis. Furthermore, metastatic CTCs were identified through a prospective five-gene signature (BCAR1, COL1A1, IGSF3, RRAD, and TFPI2). Whole-exome sequencing of CDX models and metastases further identified mutations in constitutive photomorphogenesis protein 1 (COP1) as a potential driver of metastasis. These findings illustrate the utility of the combined patient-derived CTC model and provide a glimpse of the promise of CTCs in identifying drivers of cancer metastasis.

Figure S5, Related to Figure 6. A, Assessment of SRC mRNA levels in MDA-MB-231 SRC-ORF, EMPTY-ORF, or parental cell lines. Data is normalized in RPL19 levels. B, Crystal violet staining assays on day 5 post-transfection confirms the ability of c-SRC to rescue miR-34a-induced anti-tumor growth. C-D, Examples of Pearson correlation analysis indicating MDA-MB-231 cells were not similar to BT-549 and MDA-MB-436 cells, and therefore were not included in the initial K-Means clustering analysis (results shown in D). E, The fold knockdown by miR-34a as compared to the miR-Scr treatments of the indicated genes in Clusters 1-3 in both BT-549 and MDA-MB-436 cells using a 2-fold change cut-off. None of the genes in Cluster 4 were downregulated by miR-34a (data not shown). F, Schematic of the KEGG pathway (hsa04510: Focal Adhesion) with miR-34a downregulated genes highlighted in red. G-H, Represents further analysis of the miR-34a gene signature in breast cancer. G, Indicates correlation analyses of miR-34a target genes in TNBC patients from Metabric data. H, Confirmation of prognostic importance of mIR-34a gene signature using a PROGgeneV2 algorithm on the TCGA data set.

Figure S3, Related to Figure 4. A, c-SRC expression in normal (HFF and MCF-10A), luminal-A (MCF-7), LAR-TNBC (MDA-MB-453), and mesenchymal-TNBC (MDA-MB-231, BT-549, and Hs578T) cell lines. Expression was normalized to GAPDH and made relative to c-SRC expression in HFF lines. B-C, Clonogenic assays in Hs578T (B), and MDA-MB-436 (C) TNBC cells after miR-34a transfection and treatment with Dasatnib (left panels) and paclitaxel (right panel) or as a control HeLa cells after dasatinib treatment (C, right panel). D-E, Assessment of miR-34a target genes in MDA-MB-231 cells after 72 hours of dasatinib treatment (D), or miR-34a levels after 72 hours paclitaxel treatment (E). F, miR-34a promoter luciferase assays in MDA-MB-31 cells after dasatinib treatment. G-H, Spearman rank correlation analysis of SRC levels in cell lines described in Figure 1A (G), and in all breast cancer samples in the Metabric dataset (H). I, Comparable decreases in phospho-Tyr416 active c-SRC, non-phospho-Tyr527 c-SRC, and total c-SRC are observed in MDA-MB-231 cells transfected with 15nM miR-34a versus miR-Scr control, as determined by Western blot analysis. J, Schematic highlighting the miR-34a-c-SRC double-negative feedback loop present in MSL TNBC cells, which can be influenced by exogenous addition of miR-34a, or by dasatinib treatment. * Indicates p<0.05, as compared to control conditions.

Figure S1, Related to Figure 1. A, miRNA microarray data of the top 50 most variant miRNAs across 17 breast cancer cell lines representing either basal/TNBC (top left blue bar) or luminal (top right red bar) breast cancer subgroups. Amongst these miRNAs, miR-34a (red asterisk) was found to be uniquely downregulated in basal lines. B-C, qPCR validation of array data in TNBC and Luminal-A cancer cell lines as compared to normal mammary epithelial lines (CRCs were cultured using the ROCK inhibitor and condition medium from the 3T3 feeder system as previously described(20)). D, Schematic of WebGestalt 2 analysis of Affymetrix microarray data across 19 cell lines. ¬¬miR-34a is one of several miRNAs with target enrichment in the TNBC overexpressed gene set. E, Results of hypergeometric analysis of miR-34a targets using a more stringent context score cutoff of -0.27. F, SRB growth assays on additional TNBC and normal cell lines.

Drug resistance is a major barrier against successful treatments of cancer patients. Gain of stemness under drug pressure is a major mechanism that renders treatments ineffective. Identifying approaches to target cancer stem cells (CSCs) is expected to improve treatment outcomes for patients. To elucidate the role of cancer stemness in resistance of colorectal cancer cells to targeted therapies, we developed spheroid cultures of patient-derived BRAFmut and KRASmut tumor cells and studied resistance mechanisms to inhibition of MAPK pathway through phenotypic and gene and protein expression analysis. We found that treatments enriched the expression of CSC markers CD166, ALDH1A3, CD133, and LGR5 and activated PI3K/Akt pathway in cancer cells. We examined various combination treatments to block these activities and found that a triple combination against BRAF, EGFR, and MEK significantly reduced stemness and activities of oncogenic signaling pathways. This study demonstrates the feasibility of blocking stemness-mediated drug resistance and tumorigenic activities in colorectal cancer.

Despite many advances, metastatic disease remains essentially uncurable. Thus, there is an urgent need to better understand mechanisms that promote metastasis, drive tumor evolution, and underlie innate and acquired drug resistance. Sophisticated preclinical models that recapitulate the complex tumor ecosystem are key to this process. We begin with syngeneic and patient-derived mouse models that are the backbone of most preclinical studies. Second, we present some unique advantages of fish and fly models. Third, we consider the strengths of 3D culture models for resolving remaining knowledge gaps. Finally, we provide vignettes on multiplexed technologies to advance our understanding of metastatic disease.

Figure S2, Related to Figure 2. A-F, Functional characterization of miR-34a re-introduction in additional TNBC and non-TNBC cell lines by way of Matrigel-invasion (A), soft agar growth (B), and BrdU labeling (C) experiments. For BrdU assays, we observed only a 5-10% accumulation of BrdU-positive cells 4 days post-transfection. SA-β-gal assays on MDA-MB-157 (D), and BT-20 (E, left panel) TNBC cells, as compared to MCF-7 luminal-A cells (E, right panel). F, MCF-7 cells stably transfected with either a miR-34a (miR-34a SP) or a control (Empty SP) reporter/sponge construct was assayed for SA-β-gal activity. Two independent miR-34a SP pools were generated. G, Luciferase reporter assays indicative of miR-34a activity in all TNBC, luminal, and normal cell lines used in this study. H, miRNA levels in MDA-MB-231, MDA-MB-436, and BT-549 TNBC cells or BT-474 and MCF-7 Luminal-A cells 72 hours after 10nM miR-34a or miR-Scr transfection. In TNBC cells miR-34a expressing lines harbored lower levels of miR-17/92 family members as compared to miR-Scr treated lines. * Indicates p<0.05, as compared to control conditions.

Figure S4, Related to Figure 5. A-F, Further characterization of c-SRC siRNA treatments in TNBC cell lines. A, Crystal violet staining of MDA-MB-231 and Hs578T cells post 15nM si-SRC and si-Neg transfection (Day 6 images, left panel), and quantification of staining abundance is shown on right panels). B, SRB results on Hs578T cell line. C, Analysis of a second siRNA to c-SRC in MDA-MB-231 cells. SRB assays are shown in the left panel and western blot analysis confirming c-SRC knockdown (72 hour post-transfection) is shown on the right panel. D, Crystal violet staining of HFF cells. E, SA-β-gal assays in the indicated cell lines 5 days after 15nM si-SRC transfection. F, miR-34a levels 72 hours after 15nM si-SRC transfection in Hs578T cells. G, Assessment of SRC mRNA levels in the indicated cell lines 72 hours after 15nM si-SRC transfection.

Abstract Cancer metastasis—the spread of cancer cells from a primary node to a distant site—is responsible for as much as 90% of all cancer-associated deaths due to treatment resistance and increased tumor burden. Once established, metastatic nodules oftentimes exhibit distinct molecular phenotypes from their original primary tumor, undermining gold-standard methods for determining treatments for patients, which typically rely on molecular characterization of the primary tumor. Unfortunately, a lack of robust, scalable, and appropriate models for studying differences in patient-derived primary and metastatic tumors has hindered progress in identifying metastasis-specific therapies. Previously, we reported the ability to establish in vitro cultures of circulating tumor cells (CTCs), a unique precursor population of cells that exhibits an ability to escape the primary tumor but not yet fully complete metastasis. We have since expanded the application of this GU-CTC platform to culture CTCs from the blood of patients diagnosed with a variety of metastatic cancers, resulting in the successful culture of 31 unique patient-derived CTC cell lines. Furthermore, following an initial short-term culture period, we also performed subcutaneous injection of mixed CTC cultures into immunocompromised mice, resulting in not only primary tumor formation, but also systemic metastatic nodule formation in as short as 3 months. These resulting CTC-derived xenografts (CDXs) have been demonstrated using metastatic pancreatic, colorectal, and lung adenocarcinoma-derived CTCs. Encouragingly, all CDX models also exhibited replicable metastatic patterns upon reimplantation, reinforcing the important role of CTCs as precursors to metastasis. Bulk RNA-sequencing of patient-matched whole blood, cultured CTCs, and CDX-derived primary tumor and metastatic tissues further identified enrichment of an epithelial-mesenchymal transition as well as several cancer-specific gene signatures consistent with an invasive phenotype. This extended GU-CTC platform therefore enables not only the robust and rapid expansion of CTCs through both in vitro and in vivo methods, but also offers an avenue for personalized drug screens in the effort to target cancer metastasis. Citation Format: Jerry Xiao, Richard Schlegel, Seema Agarwal. Establishing circulating tumor cell-derived xenografts following a period of in vitro culture [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5123.