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OBJECTIVE: Combined small cell lung cancer (CSCLC) with distant metastasis (DM) is an aggressive disease with a poor prognosis. Effective nomograms are needed to predict DM and early death in patients with CSCLC and DM. METHODS: This retrospective study included patients with CSCLC from the Surveillance, Epidemiology, and End Results database between 2004 and 2015. Risk factors for DM and early death were analyzed by univariate and multivariate logistic regression. Nomograms were constructed based on the results in a training cohort and confirmed in a validation cohort, and their performances were assessed by concordance index (C-index), receiver operating characteristic curve (ROC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 788 patients with CSCLC were selected, including 364 patients with metastatic CSCLC. Sex, tumor site, T stage, and N stage were independent risk factors for DM, while age, surgery, chemotherapy, and liver metastasis were independent risk factors for early death. C-index, ROC, calibration, and DCA curve analyses all showed good predictive performances for both nomograms. CONCLUSIONS: These nomograms could reliably predict DM risk in CSCLC patients and early death in CSCLC patients with DM, and may thus help clinicians to assess these risks and implement individualized therapies.

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BACKGROUND: Patients with esophageal squamous cell carcinoma (ESCC) with distant metastasis were treated with systemic chemotherapy. Recent advances in multimodal treatments have made conversion therapy a viable option for patients with incurable ESCC. OBJECTIVE: We aimed to assess the safety and efficacy of conversion therapy for ESCC with distant metastases. METHODS: Conversion therapy was defined as surgery or chemoradiotherapy (CRT) used to cure tumors that were previously considered incurable because of distant metastasis. We conducted a retrospective review of patients who underwent ESCC conversion therapy and assessed the treatment outcomes, including adverse events and survival rates. RESULTS: A total of 147 patients from 22 institutions were included. Systemic chemotherapy was initially administered to all patients. The most common M1 factor was the para-aortic lymph node, accounting for 55% of cases. Following the initial treatment, 116 patients underwent surgery, with 31 receiving CRT as conversion therapy. Postoperative complications in surgery patients included pneumonia (16%), anastomotic leakage (7%), and recurrent laryngeal nerve palsy (6%). During CRT, 18% of patients developed grade 3 or higher non-hematological toxicities. The 5-year overall survival (OS) rate was 31.7%. Pathological responders had significantly longer OS than non-responders (hazard ratio 0.493, p = 0.012). The distribution of distant metastasis, regimen type, clinical response, and conversion therapy modality did not have a significant impact on OS. CONCLUSIONS: Conversion therapy can be safely performed for ESCC with distant metastasis and has a favorable prognosis.

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Hepatocellular carcinoma (HCC), a major form of liver cancer, is characterized by high lethality and a multifactorial etiology that includes hepatitis virus infections, lifestyle factors, and genetic predispositions. This study aimed to explore the impact of ZNF208 gene polymorphisms on the clinicopathological features of Taiwanese HCC patients, focusing on three specific single nucleotide polymorphisms (SNPs): rs2188971, rs2188972, and rs8105767. Our cohort consisted of 438 HCC patients and 1193 control individuals. Clinical staging was determined using the tumor/node/metastasis (TNM) system, and various clinical indicators were collected. Our analysis revealed a statistically significant increase in ZNF208 expression in HCC patients compared to controls, indicating a potential role in HCC progression. Although no substantial association was observed between ZNF208 SNPs and increased HCC risk, specific clinical features such as distant metastasis and vascular invasion showed significant associations with these SNPs, suggesting their influence on disease aggressiveness. Demographic analyses highlighted the importance of factors like alcohol consumption and viral hepatitis markers in HCC. Our study underscores the complexity of genetic influences on HCC, with ZNF208 polymorphisms potentially affecting tumor progression and patient outcomes.

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BACKGROUND: The antigen processing machinery (APM) plays a critical role in generating tumor-specific antigens that can be recognized and targeted by the immune system. Proper functioning of APM components is essential for presenting these antigens on the surface of tumor cells, enabling immune detection and destruction. In many cancers, defects in APM can lead to immune evasion, contributing to tumor progression and poor clinical outcomes. However, the status of the APM in sarcomas is not well characterized, limiting the development of effective immunotherapeutic strategies for these patients. METHODS: We investigated 126 patients with 8 types of bone and soft tissue sarcoma operated between 2001-2021. Tissue microarrays mapped 11 specific areas in each case. The presence/absence of APM protein was determined through immunohistochemistry. Bayesian networks were used. RESULTS: All investigated sarcomas had some defects in APM. The least damaged component was HLA Class I subunit ß2-microglobulin and HLA Class II. The proteasome LMP10 subunit was defective in leiomyosarcoma (LMS), myxoid liposarcoma (MLPS), and dedifferentiated liposarcoma (DDLPS), while MHC I transporting unit TAP2 was altered in undifferentiated pleomorphic sarcoma (UPS), gastrointestinal stromal tumor (GIST), and chordoma (CH). Among different neoplastic areas, high-grade areas showed different patterns of expression compared to high lymphocytic infiltrate areas. Heterogeneity at the patient level was also observed. Loss of any APM component was prognostic of distant metastasis (DM) for LMS and DDLPS and of overall survival (OS) for LMS. CONCLUSION: Sarcomas exhibit a high degree of defects in APM components, with differences among histotypes and tumoral areas. The most commonly altered APM components were HLA Class I subunit ß2-microglobulin, HLA Class I subunit α (HC10), and MHC I transporting unit TAP2. The loss of APM components was prognostic of DM and OS and clinically relevant for LMS and DDLPS. This study explores sarcoma molecular mechanisms, enriching personalized therapeutic approaches.

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Background: Penile cancer (PC) is a rare malignant tumor, whose distant metastasis (DM) is associated with the poorest outcomes. The risk factors associated with DM and prognosis of the PC with DM remain elusive. This study was aimed at investigating risk factors associated with DM and constructing prediction models of PC with DM. Methods: This study analyzed data from the Surveillance, Epidemiology, and End Results (SEER) database over a period of 2000-2020, including clinical characteristics such as age, marital status, tumor size, Tumor Node Metastasis (TNM) staging, and treatment information. Utilizing univariate and multivariate logistic regression, alongside cox regression analysis, we identified independent risk factors for DM and prognosis in the total cases and the cases with DM. Nomograms were developed for predicting DM and prognosis in PC patients. Results: Enrolling 1,488 cases, our study identified tumor size and N stage as independent predictors of DM. The predictive nomogram for DM achieved an area under the curve (AUC) of 0.904. Notably, the 1-, 3-, and 5-year cumulative survival rates for PC with DM were 35%, 17%, and 13%, respectively, with larger tumor size associated with prognosis of PC cases with DM. This study verified a correlation between advanced age and TNM stage, as well as chemotherapy with the poor PC prognosis. The nomogram yielded 0.72, 0.69 and 0.69, in predicting 1-, 3-, and 5-year overall survivals (OS), while 0.73, 0.70 and 0.69 in predicting 1-, 3-, 5-year cancer specific survivals (CSS), respectively. Conclusions: This study investigated risk factors of PC with DM. Also, nomograms for predicting DM, OS and CSS of PC patients were developed.

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BACKGROUND: Breast cancer (BC) is the most common cancer in women and accounts for approximately 15% of all cancer deaths among women globally. The underlying mechanism of BC patients with small tumor size and developing distant metastasis (DM) remains elusive in clinical practices. METHODS: We integrated the gene expression of BCs from ten RNAseq datasets from Gene Expression Omnibus (GEO) database to create a genetic prediction model for distant metastasis-free survival (DMFS) in BC patients with small tumor sizes (≤ 2 cm) using weighted gene co-expression network (WGCNA) analysis and LASSO cox regression. RESULTS: ABHD11, DDX39A, G3BP2, GOLM1, IL1R1, MMP11, PIK3R1, SNRPB2, and VAV3 were hub metastatic genes identified by WGCNA and used to create a risk score using multivariable Cox regression. At the cut-point value of the median risk score, the high-risk score (≥ median risk score) group had a higher risk of DM than the low-risk score group in the training cohort [hazard ratio (HR) 4.51, p < 0.0001] and in the validation cohort (HR 5.48, p = 0.003). The nomogram prediction model of 3-, 5-, and 7-year DMFS shows good prediction results with C-indices of 0.72-0.76. The enriched pathways were immune regulation and cell-cell signaling. EGFR serves as the hub gene for the protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3. CONCLUSION: Prognostic gene signature was predictive of DMFS for BCs with small tumor sizes. The protein-protein interaction network of PIK3R1, IL1R1, MMP11, GOLM1, and VAV3 connected by EGFR merits further experiments for elucidating the underlying mechanisms.

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BACKGROUND AND PURPOSE: This study aims to externally validate a predictive model for distant metastasis (DM) with computed tomography (CT)-based radiomics features in prospectively enrolled non-small-cell lung cancer patients undergoing dynamic tumor-tracking stereotactic body radiation therapy (DTT-SBRT). MATERIALS AND METHODS: The study collected retrospective data from 567 patients across 11 institutions as the training dataset and prospectively enrolled 42 patients from four institutions as the external test dataset. Four clinical features were collected, and 944 CT-based radiomic features were extracted from gross tumor volumes. After standardization and feature selection, DM predictive models were developed using fine and gray regression (FG) and random survival forest (RSF), incorporating clinical and radiomic features, and their combinations within the training dataset. Then, the model was applied to the test dataset, dividing patients into high- and low-risk groups based on medians of risk scores. Model performance was assessed using the concordance index (C-index), and the statistical significance between groups was evaluated using Gray's test. RESULTS: In the training dataset, 122 of 567 patients (21.5%) developed DM, compared to 9 of 42 patients (21.4%) in the test dataset. In the test dataset, the C-indices of the clinical, radiomics, and hybrid models with FG were 0.559, 0.544, and 0.560, respectively, whereas those with RSF were 0.576, 0.604, and 0.627, respectively. The hybrid model with RSF, which exhibited the best predictive performance of all models, identified 7 of 23 patients (30.4%) as high risk and 2 of 19 patients (10.5%) as low risk for DM incidence in the test dataset (p = 0.116). CONCLUSION: Although predictive models for DM lack significance when applied to prospectively enrolled cases undergoing DTT-lung SBRT, the model with RSF exhibits a consistent capacity to effectively classify patients at a high risk of developing DM.

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BACKGROUND: In retroperitoneal leiomyosarcoma (RP LMS), the predominant issue is distant metastasis (DM). We sought to determine variables associated with this outcome and disease-specific death (DSD). METHODS: Data were retrospectively collected on patients with primary RP LMS treated at a high-volume center from 2002 to 2023. For inferior vena cava (IVC)-origin tumors, the extent of macroscopic vascular invasion was re-assessed on each resection specimen and correlated with preoperative cross-sectional imaging. Crude cumulative incidences were estimated for DM and DSD and univariable and multivariable models were performed. RESULTS: Among 157 study patients, median tumor size was 11.0 cm and 96.2% of cases were intermediate or high grade. All patients underwent complete resection, 56.7% received chemotherapy (43.9% neoadjuvant) and 14.6% received radiation therapy. Only tumor size and grade and not site of tumor origin (e.g., IVC vs. other) were associated with DM and DSD (p < 0.05). Among 64 patients with IVC-origin tumors, a novel 3-tier classification was devised based on the level of intimal disruption, which was associated with both DM (p = 0.007) and DSD (0.002). CONCLUSION: In primary RP LMS, only tumor size and grade are predictive of DM and DSD. In IVC-origin tumors, the extent of macroscopic vascular invasion is also strongly predictive of these outcomes.

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BACKGROUND: Anemia represents a well-established risk factor for patients diagnosed with gastric cancer, and is often associated with an unfavorable prognosis. In this context, the timely prediction of distant metastasis risk in patients with anemic gastric cancer assumes paramount importance. METHODS: Information of gastric cancer patients complicated with preoperative anemia in the First Affiliated Hospital of Sun Yat-sen University was collected. The cohort from the First Affiliated Hospital of Guangxi Medical University was used as an external validation set. A Nomogram was established based on the risk factors screened by univariate and multivariate logistic regression analyses. RESULTS: A total of 848 gastric cancer patients with preoperative anemia were enrolled. Pyloric obstruction, carcinoma antigen 125, T stage, N stage, tumor size, and preoperative weight loss were independent predictors of distant metastasis in gastric cancer patients with anemia (p < 0.05), based on which a nomogram was constructed. The accuracy, reliability and clinical value of the nomogram were evaluated by concordance index, receiver operating characteristic curve, decision curve analysis, calibration curve and showed good stability and clinical predictive value. CONCLUSIONS: Preoperative anemic gastric cancer patients, complicated with pyloric obstruction, elevated CA125, advanced T and N stage, larger tumor size, and preoperative weight loss, should be paid more attention to distant metastasis.

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The purpose of this study was to compare the predictive value of different lymph node staging systems and to develop an optimal prognostic nomogram for predicting distant metastasis in pancreatic ductal adenocarcinoma (PDAC). Our study involved 6364 patients selected from the Surveillance, Epidemiology, and End Results (SEER) database and 126 patients from China. Independent risk factors for distant metastasis were screened by univariate and multivariate logistic regression analyses, and a model-based comparison of different lymph node staging systems was conducted. Furthermore, we developed a nomogram for predicting distant metastasis using the optimal performance lymph node staging system. The lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), age, primary site, grade, tumor size, American Joint Committee on Cancer (AJCC) 7th Edition T stage, and radiotherapy recipient status were significant predictors of distant metastasis in PDAC patients. The model with the LODDS was a better fit than the model with the LNR. We developed a nomogram model based on LODDS and six clinical parameters. The area under the curve (AUC) and concordance index (C-index) of 0.753 indicated that this model satisfied the discrimination criteria. Kaplan-Meier curves indicate a significant difference in OS among patients with different metastasis risks. LODDS seems to have a superior ability to predict distant metastasis in PDAC patients compared with the AJCC 8th Edition N stage, PLN and LNR staging systems. Moreover, we developed a nomogram model for predicting distant metastasis. Clinicians can use the model to detect patients at high risk of distant metastasis and to make further clinical decisions.

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Objectives: Due to its rarity, there is insufficient evidence for managing ASCC patients with distant metastasis. Thus far, the therapeutic strategy for distant metastasis of ASCC is less standardized and requires a more individualized approach. Therefore, it is crucial to obtain information regarding treatment outcomes and prognostic factors following the development of distant metastasis to identify optimal care strategies for better patient outcomes and predict their prognosis. Methods: In the multi-institute cohort study conducted in Japan, we retrospectively assessed 58 ASCC patients with synchronous distant metastasis and 28 ASCC patients with metachronous distant metastasis. Results: When comparing the OS between ASCC patients with synchronous distant metastasis and metachronous distant metastasis, there was no statistically significant difference between the two groups. The OS rate at five years was 37.4% for patients with synchronous distant metastasis and 27.6%; for metachronous distant metastasis. In ASCC patients with synchronous distant metastasis, patients with distant metastasis at multiple sites exhibited extremely worse OS than those at single sites (HR: 4.56, 95% CI: 1.16-18.00, P< 0.0001). In addition, in ASCC patients with metachronous distant metastasis, early recurrence was an independent factor for predicting poor OS in the multivariate analysis (HR: 4.13, 95% CI: 1.22-13.94, P = 0.022). Conclusions: ASCC patients with distant metastasis at multiple sites were a worse prognosis. In addition, early recurrence was identified as an independent prognostic factor for OS among ASCC patients.

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BACKGROUND: Clinical findings and postoperative follow-up data on remnant gastric cancer (RGC) are limited due to its rarity. Additionally, the preoperative staging, radical surgery, and managing recurrence in RGC present significant clinical challenges. METHODS: We analyzed the clinicopathological findings, adjuvant chemotherapy, and patterns of postoperative recurrence of 313 consecutive patients who underwent curative surgery for RGC at 17 Japanese institutions. This study investigated the optimal management of RGC and the impact of adjuvant chemotherapy (AC) on recurrence-free survival (RFS). RESULTS: Pathological stages I, II, and III were observed in 55.9% (N = 175), 24.9% (N = 78), and 19.2% (N = 60) of the patients, respectively. The overall concordance rate between clinical and pathological T staging was 58.3%, with a clinical T4 sensitivity of 41.4% for diagnosing pathological T4. During the median follow-up period of 4.6 years, disease recurrence occurred in 24.3% of patients. Most recurrences (over 80%) occurred within 2.5 years, and 96.1% within 5 years after RGC surgery. Peritoneal recurrence was the most common in patients with advanced RGC, accounting for 14.1% in stage II and 28.3% in stage III. Multivariable regression analysis showed that AC was significantly associated with a longer RFS, with a hazard ratio of 0.45 (95% confidence interval: 0.26-0.76). CONCLUSIONS: Our study underscores the importance of early detection, accurate preoperative staging, and postoperative surveillance in managing advanced RGC cases. Despite some limitations, our findings indicate that AC may provide survival benefits comparable to those seen in primary gastric cancer.

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Distant metastasis of oral squamous cell carcinoma to skeletal muscles is an extremely rare entity and is an indicator of poor prognosis for the patient. We present a case of oral tongue squamous cell carcinoma that metastasized to the rectus abdominis muscle and clinically became symptomatic nine months after curative surgery of the primary.

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BACKGROUND: Patients with intermediate-risk papillary thyroid carcinoma (PTC) have a favorable prognosis with standard treatment of total thyroidectomy (TT) and adjuvant radioactive iodine therapy (RAIT). However, the benefits of TT or adjuvant RAIT remain undetermined, and they are often omitted in Japan. We investigated risk factors for life-threatening distant recurrence in patients with intermediate-risk PTC who are optimal candidates for adjuvant RAIT. PATIENTS AND METHODS: Outcomes without RAIT were retrospectively examined in 4030 intermediate-risk conventional PTC cases underwent initial surgery from 2005 to 22 (IRB approval 20200709-1). RESULTS: Lobectomy (LT) and TT was performed in 11.5% and 88.5%, respectively. Recurrent laryngeal nerve paralysis and hypoparathyroidism was less commonly observed in LT (1.3% and 0%) than TT (2.4% and 3.5 %). Fifty-six cases (1.4%) had distant recurrence. Recurrence-free survival rates at 10 years was 93.5%. There was no significant difference in recurrence rate between LT and TT. Age ≥55, cN1b, and tumor diameter >30 mm significantly associated with distant recurrence. There was a strong relationship between the number of positive risk factors and recurrence; the distant recurrence rate in cases of 0, 1, 2, and 3 positive factors was 0.3% (4/1203), 1.3% (25/1889), 2.7% (23/830) and 7.1% (4/52) (HR 6.46 (2.34-17.86), Log-rank <0.001). CONCLUSION: For intermediate-risk conventional PTC, there is no difference in prognosis even if LT was selectively conducted. However, in patients with risk factors for distant metastatic recurrence, such as age ≥55 years, cN1b, and tumor size >30 mm, adjuvant RAIT was considered eligible.

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Objective: This study aims to develop an artificial intelligence model utilizing clinical blood markers, ultrasound data, and breast biopsy pathological information to predict the distant metastasis in breast cancer patients. Methods: Data from two medical centers were utilized, Clinical blood markers, ultrasound data, and breast biopsy pathological information were separately extracted and selected. Feature dimensionality reduction was performed using Spearman correlation and LASSO regression. Predictive models were constructed using LR and LightGBM machine learning algorithms and validated on internal and external validation sets. Feature correlation analysis was conducted for both models. Results: The LR model achieved AUC values of 0.892, 0.816, and 0.817 for the training, internal validation, and external validation cohorts, respectively. The LightGBM model achieved AUC values of 0.971, 0.861, and 0.890 for the same cohorts, respectively. Clinical decision curve analysis showed a superior net benefit of the LightGBM model over the LR model in predicting distant metastasis in breast cancer. Key features identified included creatine kinase isoenzyme (CK-MB) and alpha-hydroxybutyrate dehydrogenase. Conclusion: This study developed an artificial intelligence model using clinical blood markers, ultrasound data, and pathological information to identify distant metastasis in breast cancer patients. The LightGBM model demonstrated superior predictive accuracy and clinical applicability, suggesting it as a promising tool for early diagnosis of distant metastasis in breast cancer.

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Few studies have investigated the impact of primary tumor resection (PTR) on patients with distant metastasis medullary thyroid carcinoma (DMMTC). This population-based study aims to assess the application of PTR in DMMTC patients, ascertain its benefits, and identify optimal surgical indications. DMMTC Patients diagnosed between 2010 and 2020 were included through the Surveillance, Epidemiology, and End Results (SEER) program. Logistic regression analysis identified driving factors of surgical decision-making. Propensity score matching (PSM), Kaplan-Meier method, and Cox regression were utilized to compare overall survival (OS) and disease-specific survival (DSS) between surgical and non-surgical groups. Subgroup analyses were performed to determine optimal surgical indications. Of 238 DMMTC patients included, 122 (51.3%) patients underwent PTR. Extrathyroidal extension and N1 stage emerged as independent factors promoting the surgical decision. PSM-adjusted survival analyses revealed significant advantages in both OS and DSS for the surgical group. Moreover, subgroup analyses indicated that except for patients aged ≥ 65 years, tumors ≤ 20 mm, or with multiple metastasized sites (> 1), the others significantly benefit from PTR. PTR significantly improves prognosis in selected DMMTC patients. The decision to undergo PTR in other patients should be based on a comprehensive assessment of the disease, surgeon's experience, and family discussions for potential survival benefits.

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OBJECTIVES: This study aims to investigate the clinical features of differentiated thyroid carcinoma (DTC) in children and adolescents under 18 years and assess the impact of surgery combined with thyroid hormone and radioactive iodine (RAI) on their prognosis. METHODS: A retrospective observational study was conducted, involving children/adolescents with DTC who underwent surgery at the Head and Neck Department of Tianjin Medical University Cancer Institute and Hospital from January 1998 to December 2018. RESULTS: Among 198 patients, 130 (65.7 %) were female. According to the American Thyroid Association guidelines, cases were categorized as low (106, 53.5 %), intermediate (54, 27.3 %), and high (38, 19.2 %) risk. The follow-up duration ranged from 3 to 23 years. Local recurrence and distant metastasis were identified in 21 (10.6 %) and 14 (7.1 %) cases, respectively. All patients received levothyroxine, while RAI therapy was administered to intermediate- and high-risk patients. The local recurrence and distant metastasis rates in these two groups were 33.3 and 39.5 %, respectively, with no recurrence or metastasis in the low-risk group. Persistent without structural evidence of disease were 0.9, 3.7, and 26.3 % at end of follow-up for the low-, intermediate-, and high-risk groups, respectively. The overall survival rates for all three groups were 100 %, while disease-free survival rates were 99.1, 63.0, and 34.2 % for the low-, intermediate-, and high-risk groups, respectively. CONCLUSIONS: Children/adolescents with low-risk DTC exhibited a favorable prognosis even without RAI. However, intermediate- and high-risk DTC patients, despite RAI and levothyroxine treatment, showed elevated rates of persistent disease, local recurrence, and distant metastasis.

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Background: Anaplastic thyroid cancer (ATC) is highly invasive, prone to distant metastasis (DM), and has a very poor prognosis. This study aims to construct an accurate survival prediction model for ATC patients with DM, providing reference for comprehensive assessment and treatment planning. Methods: We extracted data of ATC patients with DM diagnosed between 2004 and 2019 from the SEER database, randomly dividing them into a training set and a validation set in a ratio of 7:3. Univariate and multivariate Cox regression analyses were sequentially performed on the training set to identify independent prognostic factors for overall survival (OS) and construct nomograms for 3-month, 6-month, and 8-month OS for ATC patients with DM based on all identified independent prognostic factors. Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) curve analysis, and calibration curves were separately plotted on the training and validation sets to demonstrate the model's performance. Furthermore, patients were stratified into high- and low-risk groups based on their risk scores, and the Kaplan-Meier (KM) survival curves were used to illustrate the survival differences between the two groups. Results: A total of 322 patients were included in this study. Univariate and multivariate Cox regression analyses identified five independent prognostic factors for OS in ATC patients with DM: surgery, tumor size, age, chemotherapy, and radiotherapy. Nomograms for 3-month, 6-month, and 8-month OS were established based on these factors. The training set AUC values (3-month AUC: 0.767, 6-month AUC: 0.789, 8-month AUC: 0.795) and validation set AUC values (3-month AUC: 0.753, 6-month AUC: 0.798, 8-month AUC: 0.806) as well as the calibration curves demonstrated excellent applicability and accuracy of the model. Additionally, the DCA curves indicated substantial clinical net benefit of the model. The KM curves also confirmed the model's excellent stratification ability for patient OS. Conclusion: The nomogram developed in this study accurately predicts OS for ATC patients with DM. It can assist clinicians in formulating appropriate treatment strategies for these patients.

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PURPOSE: To perform a molecular profiling of the metastases from papillary thyroid carcinomas (PTCs) and poorly differentiated thyroid carcinomas (PDTCs). METHODS: We retrieved and analyzed the molecular and clinical features of 136 metastases from PTCs and 35 metastases from PDTCs subjected to targeted DNA sequencing, from cBioPortal. The clinicopathological data included the number and location of the metastases, and genomic data included mutations, translocations, copy number alterations and fraction of the genome altered (FGA). RESULTS: Bone metastases from PTCs had a lower frequency of BRAF mutations than the lymph node metastases (LNMs) (43% vs 88%, p < 0.01), and a higher frequency of RBM10 and NRAS mutations than the LNMs (21% vs 3% for both, p < 0.05). The FGA of the bone metastases was higher than the FGA of the lung metastases (5.6% vs 1.3%, p < 0.05). The frequency of RET translocations was higher in the lung metastases from PTCs than the LNMs (15% vs 3%, p < 0.05). The LNMs from PTC patients harboring 4 or more distant metastases (DMs) had a higher frequency of TERT promoter mutations than the LNMs from patients harboring less than 4 DMs (96% vs 65%, p < 0.001). SDHA gene amplifications were enriched in the bone metastases from PDTCs and absent in the LNMs (38% vs 0%, p < 0.05). CONCLUSION: Metastases from PTCs and PDTCs harbor clinically relevant alterations affecting distinct body locations, such as NRAS and RBM10 mutations, RET translocations and SDHA amplifications that may be explored therapeutically.