Metastasis remains the leading cause of cancer-related mortality. The concept of the pre-metastatic niche (PMN) has provided a new framework for understanding how tumors establish favorable conditions in distant organs before metastatic colonization. This review delineates the cellular and molecular hallmarks of PMN, including immune suppression, vascular/lymphatic remodeling, metabolic reprogramming, and stromal reorganization, and traces their spatiotemporal evolution from initiation to colonization. It further examines the origins of metastatic lesions, with a focus on circulating tumor cells (CTCs) and stromal stem-like cells, highlights the pivotal role of extracellular vesicles (EVs) in mediating intercellular communication, metabolic reprogramming, and therapeutic applications. Deciphering the immune and stromal determinants of PMN formation offers key mechanistic insight into organ-specific metastasis. Consequently, this review explores translational strategies targeting the PMN, such as biomarker development, spatiotemporal profiling aided by artificial intelligence (AI), and immune, metabolic, or EV-based interventions. Deciphering PMN biology is therefore poised to open new avenues for the early interception and treatment of metastasis.

Background:Lung cancer constitutes the leading cause of cancer mortality globally. This study assessed LungCanSeek, a novel blood-based protein test for lung cancer early detection. Methods:This retrospective study enrolled 1,814 participants (1,095 lung cancer, 719 non-cancer) from three different cohorts. Blood samples were analyzed for four protein tumor markers (PTMs) using Roche cobas. Artificial intelligence (AI) algorithms were developed for lung cancer detection and subtype classification: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and small cell lung cancer (SCLC). A two-step approach was modeled, using LungCanSeek for initial screening, followed by low-dose computed tomography (LDCT) for LungCanSeek's positive cases. Results:LungCanSeek achieved 83.5% sensitivity, 90.3% specificity, and 86.2% accuracy overall. Sensitivities of LUAD, LUSC, and SCLC were 83.3%, 81.4%, and 91.9%. Sensitivity increased with clinical stage in non-small cell lung cancer (NSCLC): 59.5% (I), 69.8% (II), 86.5% (III), and 91.3% (IV). Sensitivities of limited-stage and extensive-stage SCLC were 91.3% and 93.0%, respectively. The subtype classification accuracy was 77.4%. Simulation model analysis showed that the two-step approach reduced 10.3-fold false positives and 2.5-fold cost compared to LDCT for lung cancer screening in high-risk population. Conclusions:LungCanSeek is a non-invasive and cost-effective test for lung cancer early detection. The two-step approach offers a cost-effective strategy for population-wide lung cancer screening.

Recent studies highlight the promise of blood-based multicancer early detection (MCED) tests for identifying asymptomatic patients with cancer. However, most focus on a single cancer hallmark, thus limiting effectiveness because of cancer's heterogeneity. Here, a blood-based multi-omics test named SeekInCare for MCED is reported. SeekInCare incorporates multiple genomic and epigenetic hallmarks, including copy number aberration, fragment size, end motif, and oncogenic virus, via shallow whole-genome sequencing from cell-free DNA, alongside seven protein tumor markers in one tube of blood. Artificial intelligence algorithms were developed to distinguish patients with cancer from individuals without cancer and to predict the likely affected organ. The retrospective study included 617 patients with cancer and 580 individuals without cancer, covering 27 cancer types. SeekInCare achieved 60.0% sensitivity at 98.3% specificity, resulting in an area under the curve of 0.899. Sensitivities were 37.7%, 50.4%, 66.7%, and 78.1% in patients with stage I, II, III, and IV disease, respectively. Additionally, SeekInCare was evaluated in a prospective cohort consisting of 1203 individuals who received the test as a laboratory-developed test (median follow-up time, 753 days) in which it achieved 70.0% sensitivity at 95.2% specificity. The performances of SeekInCare in both retrospective and prospective studies demonstrate that SeekInCare is a blood-based MCED test, showing comparable performance to the other tests currently in development. These findings support its potential clinical utility as a cancer screening test in high-risk populations.

Lung cancer is the leading cause of cancer incidence and mortality worldwide. While low-dose computed tomography (LDCT) reduces mortality in high-risk populations, its high false-positive rate and the required specialized infrastructure and radiologists limit its application. This study assesses LungCanSeek, a novel blood-based protein test for lung cancer early detection. This retrospective study enrolled 1,814 participants (1,095 lung cancer, 719 non-cancer) from three independent cohorts. Blood samples were analyzed for four protein tumor markers (PTMs) using Roche cobas. Artificial intelligence (AI) algorithms were developed for lung cancer detection and subtype classification: lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), and small cell lung cancer (SCLC). A two-step lung cancer screening approach was modeled, using LungCanSeek for initial screening, followed by LDCT for LungCanSeek's positive cases. LungCanSeek demonstrated 83.5% sensitivity, 90.3% specificity, and 86.2% accuracy overall. Sensitivities of LUAD, LUSC, and SCLC were 83.3%, 81.4%, and 91.9%. Sensitivity increased with clinical stage in non-small cell lung cancer (NSCLC): 59.5% (I), 69.8% (II), 86.5% (III), and 91.3% (IV). For limited- and extensive-stage SCLC, sensitivities were 91.3% and 93.0%. The subtype classification accuracy was 77.4%. Compared with other blood-based lung cancer early detection tests like OncImmune’s EarlyCDT-Lung (41.0% sensitivity, 91.0% specificity) and DELFI’s FirstLook-Lung (84.0% sensitivity, 50.9% specificity), LungCanSeek showed superior performance. A screening was modeled for 9 million high-risk adults, based on the number of 15 million eligible individuals in the USA in 2024 at a 60% rate, with a 2.5% lung cancer incidence. LungCanSeek reduced false positives by 2.4-fold to 851,175 compared to 2,062,125 with LDCT. The two-step approach further cut false positives by 10.3-fold to just 200,026. LDCT’s total cost was $2,493 million, exceeding LungCanSeek’s $720 million and two-step’s $996.5 million. LungCanSeek is a non-invasive, easy to perform, cost-effective (reagent cost $15) and robust test for lung cancer early detection. The two-step approach offers a cost-effective strategy for population-wide lung cancer screening. Mao Mao, Wei Bing, Wang Wen. jian, Geng Shuai. peng, Wu Wei, Ding Chen. yu, Zhu Dan. dan, Cheng Shuo. yao, Zhao Qiu. rong, Luan Yi, Li Shi. yong. An effective and affordable blood test for lung cancer early detection using four protein markers and artificial intelligence [abstract]. In: Proceedings of the 18th AACR Conference on the Science of Cancer Health Disparities; 2025 Sep 18-21; Baltimore, MD. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2025;34(9 Suppl):Abstract nr C124.

Abstract Background: Recent studies have demonstrated that blood-based multi-cancer early detection (MCED) approaches may hold promise for identifying asymptomatic cancer patients from general population. However, most studies only exploit a single aspect of cancer hallmarks, which is challenging for the biological reasons as cancer is a heterogenous disease with a wide spectrum of pathological and clinical behaviors. Here we report a multi-omics MCED assay named SeekInCare, a CE-IVD Mark blood test, which incorporates genomic hallmarks: copy number aberrations, fragment size, end motifs and oncogenic viruses via shallow whole genome sequencing from cfDNA, and seven plasma protein tumor markers in 8 ml blood. Methods: SeekInCare was developed using several retrospective cohorts and the method has been described in a publication (DOI: 10.1016/j.jmoldx.2021.06.003) IF: 4.1 Q2. Results: We present the validation in a retrospective cohort consisting of 584 non-cancer individuals and 617 cancer patients covering 27 cancer types. SeekInCare achieved 65.5% sensitivity at 97.9% specificity, resulting in an AUC of 0.936. The sensitivities were 46.9%, 60.0%, 68.9%, 81.8% in stage I, II, III, IV patients. The sensitivities of 10 common cancer types are as the following: breast (46.2%), stomach (46.4%), colorectum (56.5%), gallbladder (60.0%), lung (62.8%), pancreas (64.7%), lymphoma (68.5%), esophagus (70.0%), liver (77.5%), and leukemia (86.7%). These cancer types account for 73.5% of cancer incidence and 81.8% of cancer-related mortality in China. We prospectively evaluated SeekInCare in a real-world cohort consisting of 1203 individuals who received the test as a laboratory developed test (median follow-up time: 753 days) in which it achieved 60.0% sensitivity, 96.1% specificity, 11.5% PPV and 99.7% NPV. Conclusion: The performances of SeekInCare in both retrospective and prospective studies demonstrate that SeekInCare is an effective blood-based MCED test with similar performance as Grail’s Galleri test, which paves the way for clinical utility as a cancer screening test in average-risk populations. Citation Format: Mao Mao, Shiyong Li, Qingqi Ren, Yi Luan, Weijie Liang, Shuaipeng Geng, Dao-Ling Huang, Dandan Zhu, Yinyin Chang, Wei Wu, Yingying Zhang, Linfeng Zhang, Yan Wang, Yumin Feng, Bing Wei, Jie Ma, Chaohui Duan, Guanghui Long. A blood-based multi-omics test for multicancer early detection: Combined retrospective and prospective studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1057.

Abstract Cancer early detection aims at reducing cancer deaths. Unfortunately, many established cancer screening methods are not suitable for use in low- and middle-income countries (LMICs) due to cost, complexity, and dependency on extensive medical infrastructure. Nearly 10,000 participants (2003 cancer cases and 7888 non-cancer cases) were divided into one training and five independent validation cohorts across different races, sample types and platforms. One tube of peripheral blood was collected from each participant and quantified using a panel of seven protein tumor markers (PTMs) consisting of AFP, CA125, CA15-3, CA19-9, CA72-4, CEA and CYFRA 21-1 by common clinical immunoassay analyzers. An algorithm named OncoSeek was established using artificial intelligence (AI) to distinguish cancer cases from non-cancer cases by calculating the probability of cancer (POC) index based on the quantification of the seven PTMs and clinical information including sex and age, and to predict the possible affected tissue of origin (TOO). The conventional clinical method that relied only on a single threshold for each PTM would make a big problem when combining the results of those markers as the false positive rate would accumulate as the number of markers increased. Nevertheless, OncoSeek was empowered by AI to significantly reduce the false positive rate, increasing the specificity from 54.0% to 93.0%. The overall sensitivity of OncoSeek was 51.7%, resulting in 84.6% accuracy. The performance was consistent in the training and the five validation cohorts from three countries (Brazil, China and United States) including two sample types (plasma and serum) and three different platforms (Roche, Luminex and ELISA). The sensitivities ranged from 39.0% to 77.6% for the detection of the nine common cancer types (breast, colorectum, liver, lung, lymphoma, oesophagus, ovary, pancreas and stomach), which account for 59.2% of global cancer deaths annually. Furthermore, it has shown excellent sensitivity in several high-mortality cancer types for which there are lacking routine screening tests in the clinic, such as the sensitivity of pancreatic cancer was 77.6%. The overall accuracy of TOO prediction in the true positives was 65.4%, which could assist the clinical diagnostic workup. OncoSeek significantly outperforms the conventional clinical method, representing a novel blood-based test for multicancer early detection (MCED) that is non-invasive, easy, efficient and robust. Moreover, the accuracy of TOO facilitates the follow-up diagnostic workup. OncoSeek is affordable (~$20) and accessible requiring nothing more than a blood draw at the screening sites, which makes it adoptable in LMICs. Citation Format: Mao Mao, Bing Wei, Qingxia Xu, Yong Shen, Raphael Brandão, Shiyong Li, Wei Wu, Pingping Xing, Yinyin Chang, Dandan Zhu. Large-scale validaton studies of a blood-based effective and affordable test for multicancer early detection [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 1269.

Nuclear protein of the testis (NUT) carcinoma is a rare and highly aggressive malignancy characterized by the rearrangement of the NUT midline carcinoma family member 1 (NUTM1) gene. Nevertheless, standardized strategies for its diagnosis and treatment remain unavailable, underscoring the need for expert consensus. To address this gap, we conducted a systematic review to gather comprehensive information on NUT carcinoma from five databases: PubMed, Web of Science, Embase, Cochrane Library, and Ovid Medline. This expert consensus was collaboratively developed by a team of international multidisciplinary experts, in partnership with the NUT Carcinoma Diagnosis Working Group of the Chinese Anti-Cancer Association’s Oncogene Diagnosis Professional Committee. This working group comprises medical oncologists, radiation oncologists, surgical oncologists, pathologists, nurses, molecular biologists, statisticians, and bioinformatics specialists. A systematic review, based on data from 526 patients across 199 articles, was conducted to comprehensively explore various characteristics, including demographic features (e.g., patient gender, distribution regions, and age), tumor-node-metastasis (TNM) classification stage, clinical symptoms, tumor size, metastatic patterns, immunohistochemical (IHC) findings, treatment modalities, prognosis-related information, and NUTM1 fusion partners. We have developed an expert consensus on diagnosing and treating NUT carcinoma using a multidisciplinary approach. The guideline provides eight recommendations, addressing epidemiological characteristics, clinical and imaging manifestations, pathological findings, IHC features, molecular mechanisms and subtypes, prognosis, diagnosis, and treatment strategies for NUT carcinoma. Furthermore, an international platform has been established to disseminate NUT carcinoma knowledge and patient recruitment, providing patients and healthcare providers access to NUT carcinoma-related information and updates on clinical trial recruitment.

156 Background: The current standard-of-care cancer screening paradigm is constrained to just a few cancer types and has challenges in patient compliance due to the invasive procedures endured from the tests. Recently studies have demonstrated that blood-based multi-cancer detection (MCED) approaches may hold promise for identifying asymptomatic cancer patients from the general population. However, most studies only exploit a single aspect of cancer hallmarks which is challenging for the biological reasons since cancer is a heterogenous disease with a wide spectrum of pathological and clinical behaviors. Methods: Here we report SeekInCare, a CE-IVD Mark MCED test, based on a novel multi-dimensional cancer risk score (CRS) model incorporating copy number aberrations, fragment size, end motifs and oncogenic viruses via shallow whole genome sequencing (sWGS) from cell-free DNA (cfDNA), and seven common tumor markers in a single 8ml blood draw. Results: Our research cohort consisted of 898 healthy subjects and 615 stage I-IV cancer patients that covered eight common cancers and 19 uncommon cancer types. The CRS model identified 427 cancer patients with 69.4% sensitivity at 98.0% specificity, resulting in an AUC (area under the curve) of 0.926. The sensitivities were 50.3%, 64.0%, 73.8% and 86.2% in stage I, II, III and IV cancers respectively. The sensitivities of eight common cancer types, breast, stomach, lung, colorectum, lymphoma, liver, pancreas and leukemia, were 45.1%, 50.0%, 63.4%, 69.4%, 70.5%, 81.4%, 82.4% and 90.9% respectively. We also prospectively evaluated SeekInCare in a real-world cohort consisting of 1212 subjects who received the test as a LDT (laboratory developed test) (median follow-up time: 753 days, range: 78~1669 days). 13 out of 18 cancer cases were detected while 46 subjects tested positive but without cancer. Thus, SeekInCare achieved 72.2% sensitivity, 96.1% specificity, 22.0% PPV and 99.6% NPV in the real-world cohort. Conclusions: In this study, we provided a non-invasive MCED test (SeekInCare) based on the multi-omics and multi-dimensional features. The case-control study demonstrated that SeekInCare could detect >20 cancer types with 69.4% sensitivity at 98.0% specificity. The outstanding real-world performance of SeekInCare warrants future investigation of its clinical utility and health economics as a mass cancer screening test in average-risk populations.

Breast cancer gene 1 (BRCA1) and BRCA2 are tumor suppressors involved in DNA damage response and repair. Carriers of germline pathogenic or likely pathogenic variants in BRCA1 or BRCA2 have significantly increased lifetime risks of breast cancer, ovarian cancer, and other cancer types; this phenomenon is known as hereditary breast and ovarian cancer (HBOC) syndrome. Accurate interpretation of BRCA1 and BRCA2 variants is important not only for disease management in patients, but also for determining preventative measures for their families. BRCA1:c.132C>T (p.Cys44=) is a synonymous variant recorded in the ClinVar database with "conflicting interpretations of its pathogenicity". Here, we report our clinical tests in which we identified this variant in two unrelated patients, both of whom developed breast cancer at an early age with ovarian presentation a few years later and had a family history of relevant cancers. Minigene assay showed that this change caused a four-nucleotide loss at the end of exon 3, resulting in a truncated p.Cys44Tyrfs*5 protein. Reverse transcription-polymerase chain reaction identified two fragments (123 and 119 bp) using RNA isolated from patient blood samples, in consistency with the results of the minigene assay. Collectively, we classified BRCA1:c.132C>T (p.Cys44=) as a pathogenic variant, as evidenced by functional studies, RNA analysis, and the patients' family histories. By analyzing variants recorded in the BRCA Exchange database, we found synonymous changes at the ends of exons could potentially influence splicing; meanwhile, current in silico tools could not predict splicing changes efficiently if the variants were in the middle of an exon, or in the deep intron region. Future studies should attempt to identify variants that influence gene expression and post-transcription modifications to improve our understanding of BRCA1 and BRCA2, as well as their related cancers.

Lung cancer ranks topmost among the most frequently diagnosed cancers. Despite increasing research, there are still unresolved mysteries in the molecular mechanism of lung cancer. Long noncoding RNA small nucleolar RNA host gene 11 (SNHG11) was found to be upregulated in lung cancer and facilitated lung cancer cell proliferation, migration, invasion, and epithelial–mesenchymal transition progression while suppressed cell apoptosis. Moreover, the high expression of SNHG11 was correlated with poor prognosis of lung cancer patients, TNM stage, and tumor size. Further assays demonstrated that SNHG11 functioned in lung cancer cells via Wnt/β‐catenin signaling pathway. Subsequently, Wnt/β‐catenin pathway was found to be activated through SNHG11/miR‐4436a/CTNNB1 ceRNA axis. As inhibiting miR‐4436 could only partly rescue the suppression of cell function induced by silencing SNHG11, it was suspected that β‐catenin might enter cell nucleus through other pathways. Mechanism investigation proved that SNHG11 would directly bind with β‐catenin to activate classic Wnt pathway. Subsequently, in vivo tumorigenesis was also demonstrated to be enhanced by SNHG11. Hence, SNHG11 was found to promote lung cancer progression by activating Wnt/β‐catenin pathway in two different patterns, implying that SNHG11 might contribute to lung cancer treatment by acting as a therapeutic target.