Fudan University Shanghai Cancer Center Research Articles

Computer-vision-based artificial intelligence for detection and recognition of instruments and organs during radical laparoscopic gastrectomy for gastric cancer: a multicenter study

Objective: To investigate the feasibility and accuracy of computer vision-based artificial intelligence technology in detecting and recognizing instruments and organs in the scenario of radical laparoscopic gastrectomy for gastric cancer. Methods: Eight complete laparoscopic distal radical gastrectomy surgery videos were collected from four large tertiary hospitals in China (First Medical Center of Chinese PLA General Hospital [three cases], Liaoning Cancer Hospital [two cases], Liyang Branch of Jiangsu Province People's Hospital [two cases], and Fudan University Shanghai Cancer Center [one case]). PR software was used to extract frames every 5-10 seconds and convert them into image frames. To ensure quality, deduplication was performed manually to remove obvious duplication and blurred image frames. After conversion and deduplication, there were 3369 frame images with a resolution of 1,920×1,080 PPI. LabelMe was used for instance segmentation of the images into the following 23 categories: veins, arteries, sutures, needle holders, ultrasonic knives, suction devices, bleeding, colon, forceps, gallbladder, small gauze, Hem-o-lok, Hem-o-lok appliers, electrocautery hooks, small intestine, hepatogastric ligaments, liver, omentum, pancreas, spleen, surgical staplers, stomach, and trocars. The frame images were randomly allocated to training and validation sets in a 9:1 ratio. The YOLOv8 deep learning framework was used for model training and validation. Precision, recall, average precision (AP), and mean average precision (mAP) were used to evaluate detection and recognition accuracy. Results: The training set contained 3032 frame images comprising 30 895 instance segmentation counts across 23 categories. The validation set contained 337 frame images comprising 3407 instance segmentation counts. The YOLOv8m model was used for training. The loss curve of the training set showed a smooth gradual decrease in loss value as the number of iteration calculations increased. In the training set, the AP values of all 23 categories were above 0.90, with a mAP of 0.99, whereas in the validation set, the mAP of the 23 categories was 0.82. As to individual categories, the AP values for ultrasonic knives, needle holders, forceps, gallbladders, small pieces of gauze, and surgical staplers were 0.96, 0.94, 0.91, 0.91, 0.91, and 0.91, respectively. The model successfully inferred and applied to a 5-minutes video segment of laparoscopic gastroenterostomy suturing. Conclusion: The primary finding of this multicenter study is that computer vision can efficiently, accurately, and in real-time detect organs and instruments in various scenarios of radical laparoscopic gastrectomy for gastric cancer.

Nomograms for metastasis of non-sentinel lymph nodes or more than three lymph nodes in patients with one or two positive sentinel lymph nodes

PurposeThe purpose of this study was to provide advice for the indication of regional nodal irradiation (RNI) in patients with one to two positive sentinel lymph nodes (SLNs) without axillary lymph node dissection (ALND).MethodsWe conducted a retrospective study in Shandong Cancer Hospital, Fudan University Shanghai Cancer Center, and West China Hospital. Logistic analysis was performed in order to explore the influencing factors of positive non-SLNs (NSLNs) and >3 positive nodes among patients with one to two SLNs+. Then, nomograms were constructed.ResultsBetween May 2010 and 2020, among the 2,845 patients with one to two SLNs+ undergoing ALND (1,992 patients in the training set and 853 patients in the validation set), there were 34.3% harbored NSLNs+ and 15.6% harbored >3 positive nodes. Multivariate analysis showed that cN stage, the number of positive/negative SLN, pathological tumor stage, lympho-vascular invasion (LVI), multicenter, and molecular subtypes were significantly associated with NSLN metastasis. Similarly, multivariate analysis also showed that cN stage, the number of positive/negative SLNs, pathological tumor stage, and LVI could be independent predictors of >3 positive nodes. Then, nomograms for NSLN metastasis and >3 positive nodes were constructed using these parameters, respectively.ConclusionsThe nomograms will be useful in estimating positive NSLNs and >3 positive nodes, and they might provide advice for the optimization of RNI.

Stability and variability of molecular subtypes: comparative analysis of primary and metastatic triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive cancer. Although our previous study classified primary TNBC into four subtypes, comprehensive longitudinal investigations are lacking. We assembled a large-scale, real-world cohort comprised of 880 TNBC patients [465 early-stage TNBC (eTNBC) and 415 metastatic TNBC (mTNBC) patients] who were treated at Fudan University Shanghai Cancer Center. The longitudinal dynamics of TNBC subtypes during disease progression were elucidated in this patient cohort. Comprehensive analysis was performed to compare primary and metastatic lesions within specific TNBC subtypes. The recurrence and metastasis rates within 3 years after initial diagnosis in the eTNBC cohort were 10.1% (47/465). The median overall survival (OS) in the mTNBC cohort was 27.2 months [95% confidence interval (CI), 24.4-30.2 months], which indicated a poor prognosis. The prognostic significance of the original molecular subtypes in both eTNBC and mTNBC patients was confirmed. Consistent molecular subtypes were maintained in 77.5% of the patients throughout disease progression with the mesenchymal-like (MES) subtype demonstrating a tendency for subtype transition and brain metastasis. Additionally, a precision treatment strategy based on the metastatic MES subtype of target lesions resulted in improved progression-free survival in the FUTURE trial. Our longitudinal study comprehensively revealed the clinical characteristics and survival of patients with the original TNBC subtypes and validated the consistency of most molecular subtypes throughout disease progression. However, we emphasize the major importance of repeat pathologic confirmation of the MES subtype.

Abstract PO3-08-10: Somatic mutations of a multigene panel in Chinese HER2-positive patients undergoing neoadjuvant therapy and impact on prognosis based on TP53 status:a single-institution retrospective cohort

Abstract Background: Gene mutations and copy number variations (CNVs) are associated with the occurrence and development of tumors. Neoadjuvant therapy (NAT) has shown greater clinical benefit in the treatment of HER2-positive breast cancer (BC). The impact of genetic mutations on NAT efficacy in BC has been frequently reported, but the relationship between genetic mutations and NAT efficacy and the long-term prognosis in HER2-positive BC patients still requires more high-quality studies. Methods: This retrospective cohort study was conducted patients receiving NAT between September 2017 and March 2021 in the Department of Breast Surgery of Fudan University Shanghai Cancer Center (FUSCC). The genomic characteristics of 513 cancer-related genes from the archived tumour blocks were assessed by next-generation sequencing (NGS). The relationship between tumour mutated gene and the postoperative pathological complete response (pCR) as well as prognosis of the disease-free survival (DFS) were further explored.Statistical methods included Chi-square test, fisher's exact test, Kaplan-Meier survival analysis, all of which were completed by SPSS 20.0. Results: 208(47.8%) patients achieved pCR after HER2-targeted NAT and 40(9.2%) patients encountered DFS events. The frequency of somatic alterations in TP53(60%), PIK3CA (15%) and ERBB2(11%) was highest in women with HER2-positive breast cancer. KMT2C (P= 0.036) and TP53(P=0.037) mutations were significantly increased in patients with DFS events. In the HER2+/HR- cohort, patients who achieved pCR had significantly benefit in prognosis (HR=3.605, P=0.002), and CCND1 amplifications(p=0.014), ATM(p=0.016) and GATA3(p=0.016) mutations were more frequent. ERBB2 mutations were significantly associated with younger ages of diagnosis(p=0.018). TP53 mutations were associated with worse DFS (HR=3.242, P=0.0110) as well as more DFS events(p=0.048). Furthermore, TP53 mutations had significant prognostic importance in HER2-positive BC patients with HR-negative (HR=3.712, P=0.0266), pCR (HR=6.253, P=0.0268) and who received trastuzumab-only targeted therapy (HR=4.145, P=0.0105). Conclusions: Regard to diverse hormone receptor status or neoadjuvant efficacy, the genetic mutation maps of Chinese HER2+ patients receiving NAT are disparate. Our study found that TP53 mutations have significant prognostic value in patients with NAT for HER2-positive BC and patients benefit differently depending on HR status, neoadjuvant regimens and response. Citation Format: Min Xiong, Liren Wangxu, Jingyan Xue, Benlong Yang, Jiong Wu. Somatic mutations of a multigene panel in Chinese HER2-positive patients undergoing neoadjuvant therapy and impact on prognosis based on TP53 status:a single-institution retrospective cohort [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-08-10.

Abstract PO5-01-05: An Open-label, Single-center Study Assessing the Efficacy of PH-based Regimen as Neoadjuvant Therapy for HER2-positive Early-stage Breast Cancer: Integrating Genomic Features and Functional Imaging

Abstract Background: Pathological complete response (pCR) has been demonstrated as a surrogate endpoint for disease-free and overall survival in HER2-positive early-stage breast cancer (EBC). Trastuzumab (H) plus pertuzumab (P) improved pCR rates in patients with HER2-positive early-stage breast cancer. Nevertheless, biomarkers to assess the effectiveness of this treatment in the neoadjuvant setting are still unclear. This study aims to evaluate the effectiveness of fluorodeoxyglucose positron emission tomography (18F-FDG-PET) and 68 Ga-Affibody HER2 Imaging PET (HER2-PET) in HER2 EBC neoadjuvant therapy, and to identify novel biomarkers for this regimen. Methods: HER2-positive EBC patients were prospectively recruited at Fudan University Shanghai Cancer Center between April 2020 and March 2022. All patients received the 1 dose of HP, followed by 6 cycles of docetaxel (T), carboplatin (Cb), and HP. We use FoundationOne to evaluate the genomic alterations before treatment. In addition, 18F-FDG-PET and HER2 PET were performed at baseline, after 1 cycle of HP, and after 6 cycles of TCbHP, to assess the effectiveness of these examinations in the prediction of pCR and correlation to disease burden. All patients were received surgery and completed 1 year of HP-based regimen in the adjuvant setting. Results: A total of 61 patients with a median age of 49 years were included. Among them, 93.5% of patients are node positive. 75.8% of the patients reported adverse events (AEs), primarily grade 1 and 2. The incidence of serious AEs was 6.6%. Patients exhibiting a greater than 40% reduction in SUVmax of 18-FDG-PET or HER2-PET scans from baseline to the fifth day after the initial HP treatment were classified as the treatment-sensitive group. The pCR rate for the 18-FDG-PET-sensitive group was 79.3%, while for the insensitive group was 48.1%. For HER2-PET scans, the pCR rate was 70.0% in the sensitive group and 59.3% in the non-sensitive group. To evaluate the potential biomarkers, 25 patients (13 pCR and 12 non-pCR) were evaluated with FoundationOne, with the identification of 1,321 somatic alterations. The most frequently altered genes were ERBB2 (100%), TP53 (96%), CDK12 (76%), MYC (56%), CCND1 (44%), PIK3CA (40%), and SRSF2 (36%). In the pCR group, we found PPM1D (38.5%) and RAD21 (38.5%) were altered more frequently than the non-pCR group. PIK3CA alterations were significantly reduced in pCR group, only 23% of cases are affected compared to 58.3% in non-pCR group. Patients were non-pCR had more MDM4 (41.7%) and ZNF217 (41.7%) alterations than pCR patients. Conclusion: The SUVmax value of 18-FDG-PET and HER2-PET scans are correlated well with the tumor burden and the residual disease in the HER2 EBCs. The reduction of SUVmax could predict pCR but need further exploration. Patients with alterations in PPM1D and RAD21 have a favorable response to the TCbHP regimen. Conversely, alterations in PIK3CA, MDM4, and ZNF217 are associated with treatment resistance. These results indicate the significance of 18-FDG-PET and HER2-PET in monitoring treatment effectiveness. The biomarker analysis in this study will help us understand the mechanism of HER2 positive breast cancer treatment resistance and assisting in tailoring personalized therapy. Clinical trial information: NCT04281641. Citation Format: Ming Chen, Benlong Yang, Sun Yuyun, Linxiaoxi Ma, Song Shaoli, Min He, Zhi-Ming Shao, Bingqiu Xiu, Jiong Wu. An Open-label, Single-center Study Assessing the Efficacy of PH-based Regimen as Neoadjuvant Therapy for HER2-positive Early-stage Breast Cancer: Integrating Genomic Features and Functional Imaging [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO5-01-05.

Abstract PS09-09: Multiomics profiling and molecular classification refine precision treatment strategies for HER2-positive breast cancer

Abstract Background: Anti-HER2 targeted therapy has achieved a series of breakthroughs. However, the current treatment strategy regarding HER2-positive breast cancer remains indiscriminate and lacks specificity, which limits the further improvement of overall treatment response and may lead to overtreatment and extra cost for some patients. Our study aims to reveal the molecular heterogeneity of HER2-positive breast cancer to guide a more precise treatment. Patients and methods: We selected HER2-positive breast cancer patients treated at Fudan University Shanghai Cancer Center between 2013 and 2014 and conducted genomic, transcriptomic, proteomic and metabolomic profiling. We then applied a non-negative matrix factorization algorithm on transcriptomic data to obtain an unsupervised classification. And we further studied the correlation between subtypes and corresponding treatment strategies in multiple cohorts of adjuvant and neoadjuvant therapy. For clinical accessibility, we developed convolutional neural network models through deep learning algorithm based on digital pathology to identify different subtypes. Additionally, we explored novel treatment strategies using the patient-derived organoids (PDOs) models. Results: We established a novel multiomics cohort of 180 HER2- breast cancer patients and classified them into four clinically significant molecular subtypes: (1) A classical HER2-enriched (HER2-CLA, N=51) subtype characterized by strong ERBB2 signaling and remarkable sensitivity to anti-HER2-targeted therapy (pathologic complete response with dual-targeted therapy: 93%). (2) an immunomodulatory (HER2-IM, N=36) subtype characterized by an immune-activated microenvironment and excellent prognosis with current treatment (no relapse in 97% of patients with a median follow-up of 86 months). Tumors of this subtype were therefore candidates for de-escalatory treatment. (3) A luminal-like (HER2-LUM, N=55) subtype distinguished by activated estrogen receptor signaling and (4) a basal/mesenchymal-like (HER2-BM, N=38) subtype enriched in activated receptor tyrosine kinase pathways. HER2-LUM and HER2- BM showed limited benefit from anti-HER2 therapy, and thus, add-on therapies might be needed. The overall area under the curve (AUC) of the convolutional neural network model based on digital pathology for identifying different subtypes is 0.77. In the exploration of novel treatment strategies, we found in the PDO model that the HER2-LUM subtype is more sensitive to a treatment regimen combining standard (chemotherapy and targeted therapy) with subsequent endocrine therapy and CDK4/6 inhibitors compared to other subtypes. Additionally, the HER2-BM subtype demonstrated greater sensitivity to treatment with a combination of EGFR inhibitors, PDGFR inhibitors or VEGFR inhibitors. Conclusion: We uncovered a high degree of molecular heterogeneity in HER2-positive breast cancer and illustrated its impact on treatment response. More precise treatment can be given according to the characteristics of different subtypes, which may achieve good efficacy and simultaneously reduce overtreatment and extra cost. The comprehensive profiling of HER2-positive breast cancers could also serve as an important resource for further exploration. Key Words: HER2-positive breast cancer cohort; molecular classification; targeted therapy; precision treatment; de-escalatory treatment. Citation Format: Yu-Wei Li, Ding Ma, Xiang-Rong Wu, Lei-Jie Dai, Shen Zhao, Yu-Zheng Xu, Xi Jin, Xiao Yi, Ying Wang, Cai-Jin Lin, Yi-Fan Zhou, Tong Fu, Wen-Tao Yang, Ming Li, Hong Lv, Yi-Zhou Jiang, Zhi-Ming Shao. Multiomics profiling and molecular classification refine precision treatment strategies for HER2-positive breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS09-09.

Abstract PO1-14-06: Integrated analysis reveals the impact of obesity on triple-negative breast cancer

Abstract Background: Obesity and overweight status, which has been growing rapidly over the past few decades, is considered as a risk factor for many types of cancers including breast cancer. Despite the multi-omics profile of triple-negative breast cancer (TNBC) has been comprehensively characterized, the impact of obesity on molecular features of TNBC is not fully appreciated. Methods: We applied an integrative analysis on clinicopathological data and molecular data (including genomic, transcriptomic, proteomic and metabolomic profiling) using the multi-omics database of TNBC (N = 465) from Fudan University Shanghai Cancer Center (FUSCC) for associations with patient body mass index (BMI). Patients were categorized into overweight/obese (OW/OB, BMI ≥ 24 kg/m2) and normal (NL, BMI < 24 kg/m2) group according to the Chinese criteria of BMI. The clinical and molecular differences between OW/OB and NL patients were systematically explored. We also constructed high-fat diet (HFD)-induced obese mouse tumor models and used single-cell RNA sequencing to investigate the impact of obesity on the tumor microenvironment. Furthermore, we analyzed the efficacy of anti-PD-1 immunotherapy on TNBC tumors in both obese and normal mice. Results: OW/OB patients exhibited higher proportion of metabolic syndrome, more adipose tissue in the breast and worse survival than NL patients. Among most frequently mutated genes, OBSCN showed statistically significantly less mutated in the OW/OB group (3.2% vs 9.6%), while TP53 (68.3% vs 76.9%) and PIK3CA (21.4% vs 14.1%) had tendency to be different. In terms of copy number alterations, we found OW/OB patients had a higher amplified or gained frequency of 13q14.11 (FOXO1) and a lower frequency of deletion or loss of chromosomal region 7p22.1 (FOXK1). We further dissect the expression profile of TNBC. Differentially expressed gene analysis and pathway enrichment analysis demonstrated that immune and metabolic pathways were the major distinction between OW/OB and NL tumors. OW/OB tumors were characterized with elevated inflammation of tumor microenvironment, as well as higher expression of immune checkpoints. Moreover, analyses focusing on metabolic heterogeneity using transcriptomic, proteomic and metabolomic data revealed upregulation of lipid metabolism and reactive oxygen species pathway in OW/OB group. In addition, our in vivo experiments demonstrated that TNBC in the obese mice displayed faster growth rates. Flow cytometry analysis and single-cell RNA sequencing showed that higher proportion of immunosuppressive myeloid cells and exhausted CD8+ T cells and upregulation of lipid metabolism in HFD group. Applying anti-PD-1 immunotherapy in both obese and normal mice displayed that tumors in the obese mice showed more sensitive to anti-PD-1 immunotherapy. Conclusion: Our study systematically revealed that obesity might play a significant role in the molecular heterogeneity of TNBC and showed distinct sensitivities to immunotherapy, which should be taken in account in the field of precision medicine. Keywords: triple-negative breast cancer, obesity, immune, tumor microenvironment, metabolism Citation Format: Yue Gong, Peng Ji, Huai-liang Wu, Li-Hua He, Ming-Liang Jin, Xin Hu, Yi-Zhou Jiang, Zhiming Shao. Integrated analysis reveals the impact of obesity on triple-negative breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-14-06.

Abstract PO1-15-09: Vitamin A Metabolism Induces Ferroptosis to Enhance Immune Therapy Efficacy in HR+/HER2- Breast Cancer

Abstract Background: Immune checkpoint blockade (ICB) has substantially improved patient overall and progression-free survival in triple-negative breast cancer (TNBC), but its efficacy remains to be elucidated in the hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) breast cancer, which is characterized by generally impotent lymphocytic infiltration. In the I-SPY2 trial (NCT01042379), pembrolizumab- or durvalumab-containing neoadjuvant therapy increased the pathologic complete response of HR+/HER2- patients. However, pembrolizumab-containing therapy failed to improve the survival of metastatic HR+/HER2- breast cancer patients (NCT03051659). These inconsistent results underscored the necessity of the investigation of predictive biomarkers to pinpoint potential ICB responders in HR+/HER2- breast cancer. Method: In this study, we collected pretreatment tumor samples from 16 patients in two respective clinical trials (NCT: 04215003 and 04355858) and profiled droplet-based single-cell sequencing, bulk RNA-Seq. Patients were treated with camrelizumab (PD-1 inhibitor)-containing therapy, and five of them achieved partial relief after an 8-week course. We also leveraged the bulk RNA-Seq data from the I-SPY2 trial and Fudan University Shanghai Cancer Center (FUSCC) TNBC ICB trials (NCT04418154 and NCT04613674) for external validation. Another FUSCC transcriptome dataset consisting of 933 treatment-naïve HR+/HER2- or TNBC breast cancer patients was used to detect the abundance of cell types. In vitro and in vivo experiments were used to explore mechanisms of anti-tumor immune response. Results: Based on the single-cell sequencing results, we comprehensively delineated the microenvironmental landscape of HR+/HER2- breast cancer. We discovered responders of immunotherapy showed a higher presence of CXCL9/10+ M1-like macrophages and exhibited enrichment of tumor cells with ferroptosis. We further identified the upregulation of vitamin A metabolism and the vitamin A metabolic gene CRABP1 in tumor cells with ferroptosis. We verified the vitamin A metabolism could induce ferroptosis in HR+/HER2- breast cancers rather than TNBC by CRABP1-ERK axis, which could further recruit CXCL9/10+ M1-like macrophages and promote anti-tumor immune response in HR+/HER2- breast cancer. Combining anti-PD1 with enhancing vitamin A metabolism via retinoid acid possessed greater therapeutic efficacy than monotherapy in HR+/HER2- breast cancers. Finally, we developed an immune therapy response score and validated its reliability in predicting the immunotherapy efficacy for HR+/HER2-breast cancers through both internal and external cohorts. Conclusion: Our study represents the earliest efforts to decipher the microenvironmental landscape and the mechanisms underlying the response to ICB in HR+/HER2- breast cancer at single-cell resolution. We unraveled a HR+/HER2- breast cancer-specific Vitamin A-ferroptosis axis that mediated immunotherapy response and constructed a robust immunotherapy efficacy prediction score based on this Vitamin A-ferroptosis axis. Citation Format: Yi-Fan Zhou, Hu-Yun-Long Zhang, Xi Jin, Yi-Zhou Jiang, Zhi-Ming Shao. Vitamin A Metabolism Induces Ferroptosis to Enhance Immune Therapy Efficacy in HR+/HER2- Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-09.

Abstract PO4-26-09: The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer

Abstract Background: Trastuzumab deruxtecan has substantially changed the treatment of HER2-low breast cancer, emphasizing the need for accurate differentiation between HER2 immunohistochemistry (IHC) scores of 0 and 1+. However, the current accuracy of HER2 IHC 0 and 1+ scoring in real-world is inadequate. Artificial intelligence (AI) has emerged as a potential solution to improve interpretation accuracy. We developed an AI algorithm based on whole slide images (WSI) to quantitatively assess HER2 expression and its role in interpreting HER2 IHC scores of 0 and 1+. Methods: Our three-phase AI analysis framework involved segmenting tumor areas (excluding ductal carcinoma in situ), detecting and classifying tumor cells based on membrane staining patterns, and grading HER2 IHC scores according to the 2018 ASCO/CAP HER2 guideline. The AI tool was trained using 6012 patches annotated by experienced pathologists. Performance evaluation was conducted using a test dataset comprising 265 slides. A total of 141 HER2 IHC slides (27 IHC 0 and 114 IHC 1+) from patients diagnosed with invasive breast cancer at Fudan University Shanghai Cancer Center in 2021 were included. Two pretrained expert pathologists independently rescored the HER2 slides, followed by analysis using the AI tool. All inconsistent cases were also reviewed by a third senior pathologist. Interobserver agreement between the pathologists and concordance between the pathologists and the AI interpretation results were assessed. We also explored potential ranges where HER2 interpretation by pathologists exhibited inconsistency or inaccuracy. Results: The HER2 AI algorithm showed high performance in interpreting all levels of HER2 expression, with an overall kappa value of 0.85. For HER2 IHC 0 and 1+ cases, the AI model demonstrated high sensitivities (0.839 and 0.914) and specificities (0.983 and 0.890) (Table 1). After the rescoring process, 51 cases were reclassified as IHC 0 and 90 cases as IHC 1+. The overall agreement rate between the historical and re-scoring results was 73.05% (103/141). The agreement rate between the AI and re-scoring results was 91.49% (129/141) (Table 2), indicating comparable interpretation capabilities between the AI model and well-trained pathologists. The interobserver agreement between the two pathologists was 83.69% (118/141), with agreement rates of 88.23% (45/51) for IHC 0 and 81.11% (73/90) for IHC 1+. Analyzing the inconsistent cases (n=12) between IHC 0 and IHC 1+, we examined the percentage of weak and incomplete expression provided by the AI. In 9 out of 12 cases, the AI provided the same results as the third senior pathologist, suggesting that AI could assist in interpretation within this range. We identified a range of 2.83% to 24.98% as a "grey-zone," where even well-trained pathologists provided inconsistent results. Conclusion: Our study demonstrates the excellent performance of an AI-based tool for scoring HER2 IHC 0 and 1+. The AI model exhibits comparable capabilities to well-trained pathologists in interpreting HER2 expression. Additionally, we identified a "grey-zone" among pathologists, highlighting the limitations of manual subjective interpretation. AI assistance within this zone may help mitigate subjective variations. Table 1. Correlation between pathologist read and AI read of HER2 immunohistochemistry. Table 2. Correlation between pathologist rescoring and AI read of HER2 immunohistochemistry. Citation Format: Ming Li, Hong Lv, Yizhi Zhao, Chenglu Zhu, Hansheng Li, Mingzhen Lin, Wen-Tao Yang. The Advantage of Artificial-Intelligence in HER2 IHC 0 and 1+ Scoring in Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO4-26-09.

Abstract PO1-15-08: Genomic characterization of triple-negative breast cancer metastases reveals PKD1 as a novel biomarker for immunotherapy

Abstract Background: While primary triple-negative breast cancer (TNBC) garners significant research attention, the genomic alterations that occur in metastasis remain insufficiently understood, especially within Asian populations. Furthermore, the genomic information obtained from the primary tumor inadequately guides metastatic cancer treatment, highlighting the critical need for in-depth investigations into metastatic TNBC. Methods: We constructed the largest cohort of TNBC metastases (n = 296) among advanced TNBC patients treated at Fudan University Shanghai Cancer Center (FUSCC) between October 2018 and December 2020. Comprehensive DNA sequencing was conducted on the collected metastatic samples to analyze genomic alterations associated with treatment response. The underlying mechanisms of specific biomarkers were also explored. Results: We presented the genomic landscape of 296 TNBC metastases, encompassing mutant genes, mutation sites and copy number variations. Through multidimensional analysis, significant disparities in TNBC were observed between Western and Asian populations, primary and metastatic tumors, as well as different metastatic sites. Notably, our findings underscore the importance of sequencing TNBC metastases to guide precision therapy, which was associated with longer progression-free survival compared to physician-chosen treatments, shedding light on the pivotal clinical value of genomic studies in metastatic settings. Furthermore, efficacy analysis suggested that PKD1 mutations enriched in metastases mediated resistance to immunotherapy. These findings were further validated through three clinical trials (NCT03805399, NCT04129996, and NCT04395989). Mechanistic studies unveiled the involvement of PKD1 in TNBC immune evasion by upregulating CCL2, thereby facilitating the recruitment of M2-type tumor-associated macrophages. Conclusion: Our study emphasizes the critical significance and necessity of genomic profiling of metastases in guiding precision therapy for TNBC. Moreover, our findings reveal PKD1 as a novel and promising biomarker for immunotherapy. Citation Format: Xiu-Zhi Zhu, Yi-Fan Zhou, Yun-Yi Wang, Xiao-Hong Ding, Xi Jin, Zhi-Ming Shao, Yi-Zhou Jiang, Zhong-Hua Wang. Genomic characterization of triple-negative breast cancer metastases reveals PKD1 as a novel biomarker for immunotherapy [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO1-15-08.

Abstract PO3-01-01: Dysregulation of Phenylalanine-tyrosine Metabolic Signaling Pathway and Neoadjuvant Response in HER2-positive Breast Cancer

Abstract Background: Although trastuzumab and tyrosine inhibitors combined with neoadjuvant chemotherapy could significantly improve patients' pathological complete response (pCR) rate, nearly half of the patients could not achieve complete remission. Our objective was to explore the relationship between metabolic signaling pathway changes and therapeutic efficacy in patients receiving neoadjuvant therapy for HER2-positive breast cancer. Methods: Core needle biopsy specimens from HER2-positive breast cancer patients who underwent neoadjuvant therapy and radical mastectomy at Fudan University Shanghai Cancer Center between January 2017 and December 2021 were collected for RNA sequencing. According to pathological evaluation, samples (n=133) were divided into pCR and non-pCR groups. Gene differences between the two groups were further evaluated for KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analysis. The TCGA (The Cancer Genome Atlas, n=1091) and the HAN ethnic GEO datasets (GSE162228, GSE206, GSE48391, n=305) were used to analyze the metabolic differences between tumors and normal tissues with patients’ prognosis. Consensus clustering analysis was performed to divide patients for low and high phenylalanine-tyrosine metabolism dysregulation to analyze patients’ outcomes. The IC50 value of cell lines was tested using CCK-8 experiments. Western blot was performed to analyze the protein level changes in mTOR and glycolysis pathway. Results: We found that phenylalanine-tyrosine metabolism was significantly enriched in HER2-positive breast cancer patients. Consensus clustering analysis of TCGA and the HAN ethnic GEO datasets showed that patients with low phenylalanine-tyrosine catabolism had a significantly worse survival outcome than patients with high tyrosine metabolism (P= 0.017). In our cohort, phenylalanine-tyrosine pathway metabolic enzyme DDC was upregulated while MAOA was downregulated in non-pCR patients compared to pCR patients, suggesting the increased production of dopamine and reduced catabolism of dopamine (DA) in non-pCR tumors. In vitro experiments showed that dopamine and the knockdown of MAOA decreased cell sensitivity to pyrotinib. In addition, dopamine and clorgyline- an MAOA inhibitor, promoted the proliferation of HER2-positive cell lines under the treatment of pyrotinib. The GSEA analysis of our neoadjuvant cohort and TCGA datasets revealed that MAOA expression was associated with an inverse enrichment of the mTORC1 and glycolysis pathways. Western blot experiment results showed that dopamine or the knockdown of MAOA could activate the mTOR and glycolysis pathway Conclusions: Phenylalanine-tyrosine metabolism was significantly enriched in HER2-positive breast cancer patients. The phenylalanine-tyrosine signaling pathway may be dysregulated in HER2-positive breast cancer and patients with low phenylalanine-tyrosine catabolism have a worse prognosis. Low expression of MAOA promotes tumor resistance to HER2-targeted drugs and could serve as a therapeutic biomarker in breast cancer. Citation Format: Chih Wan Goh, Bingqiu Xiu, Jingyan Xue, Yayun Chi, Jiong Wu. Dysregulation of Phenylalanine-tyrosine Metabolic Signaling Pathway and Neoadjuvant Response in HER2-positive Breast Cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-01-01.

Safety and efficacy of anlotinib combined with taxane and lobaplatin in neoadjuvant treatment of clinical stage II/III triple-negative breast cancer in China (the neoALTAL trial): a single-arm, phase 2 trial

Anlotinib is a new type of tyrosine kinase inhibitor that targets vascular endothelial growth factor receptors 1/2/3, platelet-derived growth factor receptors α/β, and fibroblast growth factor receptors 1-4 and c-Kit, with a broad spectrum of inhibitory effects on tumor angiogenesis and growth. It has been proven effective in HER2-negative metastatic breast cancer, but its efficacy in early-stage triple-negative breast cancer (TNBC) is unknown. This phase 2 study aims to evaluate the efficacy and safety of adding anlotinib to neoadjuvant chemotherapy in patients with TNBC. Patients with clinical stage II/III TNBC were treated with 5 cycles of anlotinib (12mg, d1-14, q3w) plus 6 cycles of taxanes (docetaxel 75 mg/m2 ,d1, q3w or nab-paclitaxel 125 mg/m2, d1 and d8, q3w) and lobaplatin (30 mg/m2, d1, q3w), followed by surgery. The primary endpoint was pathological complete response (pCR; ypT0/is ypN0) and the secondary endpoints include breast pCR (bpCR), axillary pCR (apCR), residual cancer burden (RCB), objective response rate (ORR), survival, and safety. Exploratory endpoints were efficacy biomarkers based on Fudan University Shanghai Cancer Center Immunohistochemical (FUSCC IHC) classification for TNBC and next-generation sequencing (NGS) of DNA from tumor tissue and blood samples of patients with 425-gene panel. This trial is registered with www.chictr.org.cn (ChiCTR2100043027). From Jan 2021 to Aug 2022, 48patients were assessed and 45 were enrolled. All patients received at least one dose of study treatment and underwent surgery. The median age was 48.5 years (SD: 8.7), 71% were nodal involved, and 20% had stage III. In the intention-to-treat population, 26 out of 45patients achieved pCR (57.8%; 90% CI, 44.5%-70.3%), and 39 achieved residual cancer burden class 0-I (86.7%; 95% CI, 73.2%-94.9%). The bpCR and apCR rate were 64.4% (29/45) and 71.9% (23/32), respectively. No recurrence or metastasis occurred during the short-term follow-up. Based on the FUSCC IHC-based subtypes, the pCR rates were 68.8% (11/16) for immunomodulatory subtype, 58.3% (7/12) for basal-like immune-suppressed subtype and 33.3% (4/12) for luminal androgen receptor subtype, respectively. NGS revealed that the pCR were 77% (10/13) and 50% (14/28) in MYC-amplified and wild-type patients, respectively, and 78% (7/9) and 53% (17/32) in gBRCA1/2-mutated and wild-type patients, respectively. The median follow-up time of the study was 14.9 months (95% CI: 13.5-16.3 months). There was no disease progression or death during neoadjuvant therapy. No deaths occurred during postoperative follow-up. In the safety population (N=45), Grade 3 or 4 treatment emergent adverse events occurred in 29patients (64%), and the most common events were neutropenia (38%), leukopenia (27%), thrombocytopenia (25%), anemia (13%), and hypertension (13%), respectively. The addition of anlotinib to neoadjuvant chemotherapy showed manageable toxicity and encouraging antitumor activity for patients with clinical stage II/III TNBC. Chongqing Talents Project, Chongqing Key Project of Technology Innovation and Application Development and Chongqing Outstanding Youth Natural Science Foundation.

Unveiling the potential of breast MRI: a game changer for BI-RADS 4A microcalcifications.

To assess the diagnostic performance of breast MRI for BI-RADS 4A microcalcifications on mammography and propose a potential clinical pathway to avoid unnecessary biopsies. Bibliometrics analysis of breast MRI and BI-RADS 4 was provided. A retrospective analysis was conducted on 139 women and 142 cases of BI-RADS 4A microcalcifications on mammography from Fudan University Shanghai Cancer Center. The mammographic BI-RADS level and the MRI reports were compared with the final pathological diagnosis. Much attention has been given to breast MRI and BI-RADS 4 in the literature. However, studies on BI-RADS 4A are limited. Pathological results showed 117 cases (82.4%) were benign lesions, malignant cases of 25 (17.6%) in our study. The positive predictive values (PPV), specificity, sensitivity and negative predictive values (NPV) of MRI were 44.2% (23/52), 75.2% (88/117), 92.0% (23/25), and 97.8% (88/90), respectively. Therefore, 75.2% (88/117) of biopsies for benign lesions could potentially be avoided. There were 2.2% (2/90) malignant lesions missed. Logistic regression indicated that patients who are postmenopausal (HR = 2.655, p = 0.012), have a history of breast cancer (family history) (HR = 2.833, p = 0.029), and exhibit clustered microcalcifications (HR = 2.179, p = 0.046) are more likely to have a higher MRI BI-RADS level. Breast MRI has the potential to improve the diagnosis of BI-RADS 4A microcalcifications on mammography. We propose a potential clinical pathway that patients with BI-RADS 4A on mammography who are premenopausal, have no personal history of breast cancer (family history) or have non-clustered distribution of calcifications can undergo MRI to avoid unnecessary biopsies.

Elongin B promotes breast cancer progression by ubiquitinating tumor suppressor p14/ARF

Elongin B (ELOB), a pivotal element in the ELOB/c-Cullin2/5-SOCS-box E3 ubiquitin-protein ligase complex, plays a significant role in catalyzing the ubiquitination and subsequent degradation of a broad spectrum of target proteins. Notably, it is documented to facilitate these processes. However, the regulatory role of ELOB in breast cancer remains ambiguous. In this study, through bio-informatic analysis of The Cancer Genome Atlas and Fudan University Shanghai Cancer Center database, we demonstrated that ELOB was over-expressed in breast cancer tissues and was related to unfavorable prognosis. Additionally, pathway enrichment analysis illustrated that high expression of ELOB was associated with multiple cancer promoting pathways, like cell cycle, DNA replication, proteasome and PI3K − Akt signaling pathway, indicating ELOB as a potential anticancer target. Then, we confirmed that both in vivo and in vitro, the proliferation of breast cancer cells could be significantly suppressed by the down-regulation of ELOB. Mechanically, immunoprecipitation and in vivo ubiquitination assays prompted that, as the core element of Cullin2-RBX1-ELOB E3 ligase (CRL2) complex, ELOB regulated the ubiquitination and the subsequent degradation of oncoprotein p14/ARF. Moreover, the anticancer efficacy of erasing ELOB could be rescued by simultaneous knockdown of p14/ARF. Finally, through analyzing breast cancer tissue microarrays and western blot of patient samples, we demonstrated that the expression of ELOB in tumor tissues was elevated in compared to adjacent normal tissues. In conclusion, ELOB is identified to be a promising innovative target for the drug development of breast cancer by promoting the ubiquitination and degradation of oncoprotein p14/ARF.Graphical headlightsELOB is highly expressed in breast cancer.High ELOB levels were positively associated with poor prognosis.ELOB promotes p14/ARF degradation as part of the Cullin2-RBX1-ELOB E3 ligase complex.ELOB is a promising biomarker for breast cancer.Graphical

Development of an Interpretable Deep Learning Model for Pathological Tumor Response Assessment After Neoadjuvant Therapy.

Neoadjuvant therapy followed by surgery has become the standard of care for locally advanced esophageal squamous cell carcinoma (ESCC) and accurate pathological response assessment is critical to assess the therapeutic efficacy. However, it can be laborious and inconsistency between different observers may occur. Hence, we aim to develop an interpretable deep-learning model for efficient pathological response assessment following neoadjuvant therapy in ESCC. This retrospective study analyzed 337 ESCC resection specimens from 2020-2021 at the Pudong-Branch (Cohort 1) and 114 from 2021-2022 at the Puxi-Branch (External Cohort 2) of Fudan University Shanghai Cancer Center. Whole slide images (WSIs) from these two cohorts were generated using different scanning machines to test the ability of the model in handling color variations. Four pathologists independently assessed the pathological response. The senior pathologists annotated tumor beds and residual tumor percentages on WSIs to determine consensus labels. Furthermore, 1850 image patches were randomly extracted from Cohort 1 WSIs and binarily classified for tumor viability. A deep-learning model employing knowledge distillation was developed to automatically classify positive patches for each WSI and estimate the viable residual tumor percentages. Spatial heatmaps were output for model explanations and visualizations. The approach achieved high concordance with pathologist consensus, with an R^2 of 0.8437, a RAcc_0.1 of 0.7586, a RAcc_0.3 of 0.9885, which were comparable to two senior pathologists (R^2 of 0.9202/0.9619, RAcc_0.1 of 8506/0.9425, RAcc_0.3 of 1.000/1.000) and surpassing two junior pathologists (R^2 of 0.5592/0.5474, RAcc_0.1 of 0.5287/0.5287, RAcc_0.3 of 0.9080/0.9310). Visualizations enabled the localization of residual viable tumor to augment microscopic assessment. This work illustrates deep learning's potential for assisting pathological response assessment. Spatial heatmaps and patch examples provide intuitive explanations of model predictions, engendering clinical trust and adoption(Code and data will be available at https://github.com/WinnieLaugh/ESCC_Percentage once the paper has been conditionally accepted). Integrating interpretable computational pathology could help enhancethe efficiency and consistency of tumor response assessment and empower precise oncology treatment decisions.

Colorectal adenocarcinoma with enteroblastic differentiation: a clinicopathological analysis of eight cases

Objective: To investigate the clinicopathological features of colorectal adenocarcinoma with enteroblastic differentiation (CAED). Methods: Eight cases of CAED diagnosed at the Department of Pathology, Fudan University Shanghai Cancer Center, Shanghai, China from January 2017 to August 2023 were collected. The histopathological, immunohistochemical, molecular and prognostic features of 8 CAED cases were analyzed. The relevant studies were also reviewed. Results: Among the eight patients, there were six males and two females, with an average age of 58 years (range: 29-77 years, median age: 61.5 years). Preoperative serum alpha-fetoprotein levels were elevated in five patients (14.0-286.6 μg/L). Four tumors were located in the colon, and four tumors in the rectum. Two patients were clinically staged as advanced stage (stage Ⅳ), and distant metastasis occurred at the initial diagnosis (one case had liver metastasis, and the other had lung, bone and multiple lymph nodes metastases). Six patients were clinically staged as locally-advanced stage (Stage Ⅱ-Ⅲ). Three of them developed distant metastases after surgery (one case had liver metastasis, one case had lung metastasis, and one case had peritoneal metastasis). Additionally, two patients died at 9 months and 24 months after surgery, respectively. The tumors were composed of various proportions of adenocarcinoma components with enteroblastic differentiation (30%-100%) and classical tubular adenocarcinoma components. The component with enteroblastic differentiation exhibited morphology similar to embryonic intestinal epithelium: cuboidal or columnar tumor cells arranged in tubular, papillary, cribriform, or solid nest patterns, with clear cytoplasm. Immunohistochemical studies showed that tumor cells expressed at least one oncofetal protein (SALL4, Glypican-3, and AFP). In addition, focal squamous differentiation was observed in 3 cases (3/8). Compared to the primary tumor, both CAED and squamous differentiation components were increased in the metastatic tumors. Based on the sequencing results of KRAS, NRAS and BRAF of the primary and/or metastatic tumors, 5 cases were wild-type, while KRAS exon 2 (G13D) mutations were identified in 2 cases. Conclusions: CAED is a rare colorectal malignancy with a dismal prognosis. Accurate pathological diagnosis is prognostically valuable. The histological features of enteroblastic differentiation, elevated serum AFP levels, and the expression of oncofetal proteins play an important role in the tumor diagnosis.

Assessing the effectiveness and safety of surufatinib versus everolimus or sunitinib in advanced neuroendocrine neoplasms: insights from a real-world, retrospective cohort study using propensity score and inverse probability treatment weighting analysis.

While surufatinib, sunitinib, and everolimus have shown efficacy for advanced neuroendocrine neoplasms (NENs) in randomized controlled trials (RCTs), direct comparisons in a real-world setting remain unexplored. This gap highlights the clinical need to understand their comparative effectiveness and safety within the diverse Chinese population. Addressing this, our study provides insights into the real-world performance of these therapies, aiming to inform treatment selection and improve patient outcomes. A retrospective, observational study was conducted at Fudan University Shanghai Cancer Center, including patients with advanced NENs treated with surufatinib, sunitinib, or everolimus between July 2020 and April 2023. Eligibility criteria focused on histologically confirmed, locally advanced, unresectable, or metastatic NENs, with patients having received at least one month of targeted therapy. We employed inverse probability weighting (IPW) with the propensity score (PS) matching to adjust for the bias of baseline characteristics. The assessment of covariates included age, sex, performance status, primary tumor site, functional status, genetic mutations, tumor differentiation, Ki67 index, tumor grade, metastasis site, and previous therapies. The primary outcome was progression-free survival (PFS), and secondary outcomes included objective response rate (ORR), disease control rate (DCR), and adverse events (AEs). The study enrolled 123, 56, and 68 locally advanced or metastatic NEN patients treated with surufatinib, sunitinib, and everolimus, respectively. Before adjusting for confounding factors, surufatinib was used less frequently as a first-line treatment compared to sunitinib and everolimus in pancreatic NENs (pNENs) (11.1% vs. 22.1%, P=0.057). Significant differences were noted in prior treatments and tumor characteristics between surufatinib and everolimus groups in extrapancreatic NENs (epNENs) (P<0.05). Post-IPW, these disparities were resolved (P>0.05). Surufatinib demonstrated superior median PFS (mPFS) in both pancreatic [8.30 vs. 6.33 months, hazard ratio (HR) 0.592, P<0.001] and epNENs (8.73 vs. 3.70 months, HR 0.608, P<0.001) compared to everolimus or sunitinib. Notably, male gender (HR 1.75, P=0.001), functional status (HR 2.09, P=0.01), Ki67 index >20% (HR 12.7, P=0.004), previous somatostatin analogue (SSA) treatment (HR 1.73, P=0.001), germline mutation (HR 5.62, P<0.001), poor differentiation (HR 7.45, P<0.001), liver metastasis (HR 1.72, P=0.001) and multiple treatment lines (HR 1.62 for 2nd line, P=0.04; HR 1.88 for ≥3rd line, P=0.01) were identified as negative prognostic factors for PFS. Conversely, dose adjustment (HR 0.63, P=0.009) and treatment with surufatinib (HR 0.58 for pNEN, P<0.001; HR 0.62 for epNEN, P=0.002) were correlated with longer PFS. In a real-world Chinese cohort, surufatinib significantly outperformed sunitinib and everolimus in prolonging PFS among advanced NEN patients, with identifiable clinical features impacting survival, and conclusions regarding superiority should be interpreted with caution due to the retrospective design. Our findings underscore the need for prospective studies to further validate these results and explore additional predictive biomarkers for personalized treatment strategies.

Synchronous papillary and follicular thyroid carcinomas: the first retrospective cohort study and literature review.

Papillary thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC) contribute to more than 95% of thyroid malignancies. However, synchronous PTC and FTC are less common; it is most commonly discovered incidentally as synchronous malignancies during operation, which adds difficulties to intraoperative decision-making and postoperative treatment. Therefore, we analyzed the clinicopathological characteristics and prognosis of patients with PTC and FTC in our center. We conducted a search of single PTC, single FTC, and synchronous PTC/FTC patients who received initial surgery treatment at Fudan University Shanghai Cancer Center from 2006 to 2018 and collected paraffin-embedded samples of synchronous patients. Clinicopathological characteristics were collected from the electronic medical record system. Follow-up was performed through telephone contact or medical records. Exome sequencing was performed by ThyroLead panel. Total of 42 synchronous PTC/FTC patients, 244 single FTC patients, and 2,959 single PTC patients were included. It showed a similarity between the clinicopathological features of synchronous thyroid cancer patients and single PTC patients, with a greater proportion of females, higher probabilities of lymph node metastasis, and higher rate of concurrence of Hashimoto's disease. The disease-free survival (DFS) curve indicated a worse prognosis of the synchronous group and single PTC group compared to the single FTC group, who had a propensity for neck lymph node recurrence; however, logistic multivariate regression analysis did not find any factor related to recurrence in the synchronous group. After re-checking pathology, DNA extraction, and quality control, genetic alteration information of 62 samples including primary tumors and metastatic lymph nodes from 35 synchronous cancer patients was displayed. In total, 81 mutations and 1 fusion gene were identified, including mutations related to outcomes and targeted therapy. Besides, some rare mutations in thyroid cancer were found in these patients. To conclude, synchronous PTC/FTC tend to be incidentally discovered during or after operation, behaving more like single PTC. The prognosis of synchronous patients is worse than that of single FTC patients and supplemental cervical lymph node dissection, total thyroidectomy, and postoperative radioiodine therapy should be taken into consideration after diagnosis. The next-generation sequencing (NGS) showed a unique molecular feature of synchronous patients with some rare mutations.

Association of preoperative and recurrent serum carcinoembryonic antigen and outcome of colorectal cancer patients with metastatic relapse

BackgroundSeldom have the associations of preoperative CEA (p-CEA) and recurrent CEA (r-CEA) levels as well as changes in p-CEA and r-CEA with survival in patients with stage I–III colorectal cancer (CRC) who have experienced metastatic relapse, been thoroughly examined. Methods241 consecutive patients with stage I–III CRC who experienced metastatic relapse at Fudan University Shanghai Cancer Center (FUSCC) between January 2008 and January 2016 were investigated. The influence of p-CEA, r-CEA and CEA alteration on the overall survival (OS) and relapse-to-death survival (RDS) was evaluated. The restricted cubic spline regression model was employed to explore the optimal cut-off value of CEA. ResultsAll 241 patients were categorized into four groups built on their CEA alteration patterns as follows: A, patients presenting elevated p-CEA levels but normal r-CEA levels (P–N); B, patients displaying normal levels of both p-CEA and r-CEA (N–N); C, patients exhibiting elevated levels of both p-CEA and r-CEA (P–P); D, patients with normal p-CEA levels but elevated r-CEA levels (N–P). The correlation between p-CEA and OS (P = 0.3266) and RDS (P = 0.2263) was insignificant. However, r-CEA exhibited a significant association with both OS (P = 0.0005) and RDS (P = 0.0002). Group A demonstrated the longest OS and RDS, whereas group D exhibited the poorest OS and RDS outcomes. For both OS and RDS, the CEA alteration groups served as an independent prognostic indicator. The optimal cut-off threshold for CEA was determined to be 5.1 ng/ml via the restricted cubic spline regression model. Conclusionr-CEA has a stronger correlation with OS and RDS in individuals with stage I–III CRC who have experienced metastatic relapse.The change between p-CEA and r-CEA could further indicate post-relapse survival, thereby facilitating the assessment of mortality risk stratification in stage I-III CRC patients experiencing metastatic relapse.

Identification of immune-related prognostic biomarkers in triple-negative breast cancer.

Triple-negative breast cancer (TNBC), a type of breast cancer, lacks immune-related markers that can be used for prognosis or prediction. Therefore, we created a predictive framework for TNBC using a risk assessment. Our previous study group consisted of 360 individuals who were diagnosed with TNBC through pathology using RNA sequencing and had clinical data from Fudan University Shanghai Cancer Center (FUSCC). A risk scoring model was constructed using the Cox regression method with the least absolute shrinkage and selection operator (LASSO). A multivariate Cox regression analysis was utilized to develop the prediction model, which was then assessed using the consistency index and calibration plots. The validation cohort of The Cancer Genome Atlas (TCGA) TNBC confirmed the strength of the signatures' predictive value. The prognostic risk score model included 12 genes: TDO2, CHIT1, CARML2, HLA-C, ADIRF, C19orf33, CA8, AHNAK2, RHOV, OPLAH, THEM6, and NEBL. The receiver operator characteristic (ROC) curves for survivability values at 1, 3, and 5 years in the FUSCC TNBC cohort demonstrated area under the curve (AUC) values of 0.78, 0.83, and 0.75, respectively. These results indicated a high level of accuracy in predicting outcomes, which was further confirmed through validation using TCGA database. The patients in the high-risk group showed worse prognoses and lower levels of immune cell infiltration, specifically CD8+ T cells, than those in the low-risk group. Furthermore, the low-risk group exhibited a significant upregulation of genes that encode immune checkpoints, including CD274 and CTLA4, suggesting that immunotherapy may yield enhanced efficacy within this particular group. In conclusion, the prognostic signature consisting of 12 genes can assist in the choice of immunotherapy for TNBC.